{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "thorough-brake",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'random_geom': (2000, 0.05, 'r_g'),\n",
       " 'random_geom_50': (50, 0.15, 'r_g'),\n",
       " 'Erdős–Rényi': (2000, 15000, 'gnm'),\n",
       " 'WS1': (2000, [15, 0], 'WS'),\n",
       " 'WS2': (2000, [15, 0.01], 'WS'),\n",
       " 'WS3': (2000, [15, 1], 'WS'),\n",
       " 'BA': (2000, 7, 'BA'),\n",
       " 'complete': (2000, 100500, 'complete')}"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import networkx\n",
    "import scipy.sparse as sprs\n",
    "import numpy as np\n",
    "#import scipy.sparse\n",
    "import scipy.sparse as sprs\n",
    "import copy \n",
    "import random as r_n\n",
    "import pylab\n",
    "from random import randint \n",
    "from matplotlib import mlab\n",
    "from scipy.stats import bernoulli\n",
    "from scipy.optimize import minimize\n",
    "import pandas as pd\n",
    "from scipy.sparse import csr_matrix, lil_matrix, hstack, vstack\n",
    "import random\n",
    "from tqdm.auto import tqdm\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import preprocessing \n",
    "from sklearn.preprocessing import normalize\n",
    "from random import choice\n",
    "from scipy.stats import binom\n",
    "import os\n",
    "from sklearn.model_selection import ParameterGrid\n",
    "from multiprocessing import Process\n",
    "from IPython.display import clear_output\n",
    "from statsmodels.stats.proportion import proportion_confint\n",
    "from IPython.display import clear_output\n",
    "import math\n",
    "from scipy import integrate\n",
    "import seaborn as sns\n",
    "from IPython.display import clear_output\n",
    "import time\n",
    "from sympy import Symbol\n",
    "from sympy import *\n",
    "from scipy.optimize import minimize, rosen, rosen_der\n",
    "import pickle\n",
    "\n",
    "from Model import experiment_one_matrix, experiment_two_matrices, save, load, save_noise, right_part, all_right_parts, load_noise\n",
    "\n",
    "topologies = {}\n",
    "\n",
    "topologies['random_geom'] = (2000, 0.05, 'r_g')\n",
    "topologies['random_geom_50'] = (50, 0.15, 'r_g')\n",
    "topologies['Erdős–Rényi'] = (2000, 15000, 'gnm')\n",
    "topologies['WS1'] = (2000, [15, 0], 'WS')\n",
    "topologies['WS2'] = (2000, [15, 0.01], 'WS')\n",
    "topologies['WS3'] = (2000, [15, 1], 'WS')\n",
    "topologies['BA'] = (2000, 7, 'BA')\n",
    "topologies['complete'] = (2000, 100500, 'complete')\n",
    "\n",
    "topologies"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "monthly-register",
   "metadata": {},
   "source": [
    "# Prepare mean-field predictions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "useful-statement",
   "metadata": {},
   "source": [
    "# Scenario 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "egyptian-taiwan",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alpha=0 beta=0 psi=0 phi=0 True\n",
      "0.643 0.357\n",
      "13.826 -12.826\n",
      "\n",
      "\n",
      "alpha=0 beta=0 psi=0.01 phi=0 False\n",
      "-13.779 14.779\n",
      "0.623 0.377\n",
      "\n",
      "\n",
      "alpha=0 beta=0 psi=0.02 phi=0 False\n",
      "-3.312 4.312\n",
      "0.599 0.401\n",
      "\n",
      "\n",
      "alpha=0 beta=0 psi=0.03 phi=0 False\n",
      "-1.355 2.355\n",
      "0.565 0.435\n",
      "\n",
      "\n",
      "alpha=0 beta=0 psi=0.04 phi=0 False\n",
      "-0.495 1.50\n",
      "0.513 0.487\n",
      "\n",
      "\n",
      "alpha=0 beta=0 psi=0.048 phi=0 False\n",
      "-0.042 1.0\n",
      "0.433 0.567\n",
      "\n",
      "\n",
      "alpha=0 beta=0 psi=0.049 phi=0 False\n",
      "0.0 1\n",
      "0.420 0.580\n",
      "\n",
      "\n",
      "alpha=0.005 beta=0 psi=0 phi=0 True\n",
      "0.674 0.326\n",
      "6.895 -5.895\n",
      "\n",
      "\n",
      "alpha=0.005 beta=0 psi=0.01 phi=0 True\n",
      "0.656 0.344\n",
      "121.457 -120.457\n",
      "\n",
      "\n",
      "alpha=0.005 beta=0 psi=0.02 phi=0 False\n",
      "-4.773 5.773\n",
      "0.634 0.366\n",
      "\n",
      "\n",
      "alpha=0.005 beta=0 psi=0.03 phi=0 False\n",
      "-1.596 2.596\n",
      "0.603 0.397\n",
      "\n",
      "\n",
      "alpha=0.005 beta=0 psi=0.04 phi=0 False\n",
      "-0.535 1.54\n",
      "0.556 0.444\n",
      "\n",
      "\n",
      "alpha=0.005 beta=0 psi=0.048 phi=0 False\n",
      "-0.042 1.0\n",
      "0.485 0.515\n",
      "\n",
      "\n",
      "alpha=0.005 beta=0 psi=0.049 phi=0 False\n",
      "0.0 1\n",
      "0.474 0.526\n",
      "\n",
      "\n",
      "alpha=0.01 beta=0 psi=0 phi=0 True\n",
      "0.714 0.286\n",
      "4.412 -3.412\n",
      "\n",
      "\n",
      "alpha=0.01 beta=0 psi=0.01 phi=0 True\n",
      "0.698 0.302\n",
      "10.125 -9.1250\n",
      "\n",
      "\n",
      "alpha=0.01 beta=0 psi=0.02 phi=0 False\n",
      "-9.402 10.40\n",
      "0.678 0.322\n",
      "\n",
      "\n",
      "alpha=0.01 beta=0 psi=0.03 phi=0 False\n",
      "-1.986 2.986\n",
      "0.651 0.349\n",
      "\n",
      "\n",
      "alpha=0.01 beta=0 psi=0.04 phi=0 False\n",
      "-0.586 1.59\n",
      "0.611 0.389\n",
      "\n",
      "\n",
      "alpha=0.01 beta=0 psi=0.048 phi=0 False\n",
      "-0.043 1.0\n",
      "0.554 0.446\n",
      "\n",
      "\n",
      "alpha=0.01 beta=0 psi=0.049 phi=0 False\n",
      "0.0 1\n",
      "0.546 0.454\n",
      "\n",
      "\n",
      "alpha=0.015 beta=0 psi=0 phi=0 True\n",
      "0.766 0.234\n",
      "3.109 -2.109\n",
      "\n",
      "\n",
      "alpha=0.015 beta=0 psi=0.01 phi=0 True\n",
      "0.753 0.247\n",
      "4.910 -3.910\n",
      "\n",
      "\n",
      "alpha=0.015 beta=0 psi=0.02 phi=0 True\n",
      "0.737 0.263\n",
      "80.246 -79.246\n",
      "\n",
      "\n",
      "alpha=0.015 beta=0 psi=0.03 phi=0 False\n",
      "-2.754 3.754\n",
      "0.717 0.283\n",
      "\n",
      "\n",
      "alpha=0.015 beta=0 psi=0.04 phi=0 False\n",
      "-0.655 1.66\n",
      "0.686 0.314\n",
      "\n",
      "\n",
      "alpha=0.015 beta=0 psi=0.048 phi=0 False\n",
      "-0.043 1.0\n",
      "0.647 0.353\n",
      "\n",
      "\n",
      "alpha=0.015 beta=0 psi=0.049 phi=0 False\n",
      "0.0 1\n",
      "0.642 0.358\n",
      "\n",
      "\n",
      "alpha=0.02 beta=0 psi=0 phi=0 True\n",
      "0.842 0.158\n",
      "2.273 -1.273\n",
      "\n",
      "\n",
      "alpha=0.02 beta=0 psi=0.01 phi=0 True\n",
      "0.835 0.165\n",
      "3.00000000000000 -2.00000000000000\n",
      "\n",
      "\n",
      "alpha=0.02 beta=0 psi=0.02 phi=0 True\n",
      "0.826 0.174\n",
      "6.352 -5.352\n",
      "\n",
      "\n",
      "alpha=0.02 beta=0 psi=0.03 phi=0 False\n",
      "-5.108 6.108\n",
      "0.814 0.186\n",
      "\n",
      "\n",
      "alpha=0.02 beta=0 psi=0.04 phi=0 False\n",
      "-0.756 1.76\n",
      "0.799 0.201\n",
      "\n",
      "\n",
      "alpha=0.02 beta=0 psi=0.048 phi=0 False\n",
      "-0.044 1.0\n",
      "0.782 0.218\n",
      "\n",
      "\n",
      "alpha=0.02 beta=0 psi=0.049 phi=0 False\n",
      "0.0 1\n",
      "0.780 0.220\n",
      "\n",
      "\n",
      "alpha=0.024 beta=0 psi=0 phi=0 True\n",
      "0.949 0.0510\n",
      "1.743 -0.7430\n",
      "\n",
      "\n",
      "alpha=0.024 beta=0 psi=0.01 phi=0 True\n",
      "0.948 0.0520\n",
      "2.100 -1.100\n",
      "\n",
      "\n",
      "alpha=0.024 beta=0 psi=0.02 phi=0 True\n",
      "0.946 0.0540\n",
      "3.205 -2.205\n",
      "\n",
      "\n",
      "alpha=0.024 beta=0 psi=0.03 phi=0 False\n",
      "-38.668 39.668\n",
      "0.945 0.0551\n",
      "\n",
      "\n",
      "alpha=0.024 beta=0 psi=0.04 phi=0 False\n",
      "-0.884 1.88\n",
      "0.943 0.0570\n",
      "\n",
      "\n",
      "alpha=0.024 beta=0 psi=0.048 phi=0 False\n",
      "-0.044 1.0\n",
      "0.942 0.0580\n",
      "\n",
      "\n",
      "alpha=0.024 beta=0 psi=0.049 phi=0 False\n",
      "0.0 1\n",
      "0.942 0.0580\n",
      "\n",
      "\n",
      "alpha=0.025 beta=0 psi=0 phi=0 True\n",
      "1.00000000000000 0\n",
      "1.593 -0.5930\n",
      "\n",
      "\n",
      "alpha=0.025 beta=0 psi=0.01 phi=0 True\n",
      "1.00000000000000 0\n",
      "1.881 -0.8810\n",
      "\n",
      "\n",
      "alpha=0.025 beta=0 psi=0.02 phi=0 True\n",
      "1.00000000000000 0\n",
      "2.712 -1.712\n",
      "\n",
      "\n",
      "alpha=0.025 beta=0 psi=0.03 phi=0 True\n",
      "1.00000000000000 0\n",
      "30.798 -29.798\n",
      "\n",
      "\n",
      "alpha=0.025 beta=0 psi=0.04 phi=0 False\n",
      "-0.934 1.93\n",
      "1.00000000000000 0\n",
      "\n",
      "\n",
      "alpha=0.025 beta=0 psi=0.048 phi=0 False\n",
      "-0.044 1.0\n",
      "1.00000000000000 0\n",
      "\n",
      "\n",
      "alpha=0.025 beta=0 psi=0.049 phi=0 False\n",
      "0.0 1\n",
      "1.00000000000000 0\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "m=2\n",
    "\n",
    "table_mean_field_approx = []\n",
    "\n",
    "beta = 0\n",
    "phi = 0\n",
    "\n",
    "for alpha in [0, 0.005, 0.01, 0.015, 0.02, 0.024, 0.025]:\n",
    "    for psi in [0, 0.01, 0.02, 0.03, 0.04, 0.048, 0.049]:\n",
    "\n",
    "        #load transition matrix\n",
    "        transition_matrix = []\n",
    "        for i in range(m):\n",
    "            transition_matrix.append(np.load(f'Transition matrices/Matrix_{m}_{i+1}.npy'))\n",
    "            #transition_matrix.append(np.load(f'Transition matrices/Matrix_{m}_{i+1}_second_iteration.npy'))\n",
    "\n",
    "        transition_matrix[0] = transition_matrix[0].T\n",
    "        transition_matrix[1] = transition_matrix[1].T\n",
    "\n",
    "        if alpha != 0.025:\n",
    "            transition_matrix[0][0, 0] += alpha\n",
    "            transition_matrix[0][0, 1] -= alpha\n",
    "        else:\n",
    "            transition_matrix[0][0, 0] = 1\n",
    "            transition_matrix[0][0, 1] = 0\n",
    "\n",
    "        if psi != 0.049:\n",
    "            transition_matrix[1][1, 0] -= psi\n",
    "            transition_matrix[1][1, 1] += psi\n",
    "        else:\n",
    "            transition_matrix[1][1, 0] = 0\n",
    "            transition_matrix[1][1, 1] = 1                       \n",
    "        \n",
    "        \n",
    "        if (phi == 0) & (beta == 0.018):\n",
    "            transition_matrix[0][1, 0] = transition_matrix[1][0, 1]\n",
    "            transition_matrix[0][1, 1] = transition_matrix[1][0, 0]\n",
    "        else:\n",
    "            transition_matrix[0][1, 0] -= beta\n",
    "            transition_matrix[0][1, 1] += beta\n",
    "            transition_matrix[1][0, 0] += phi\n",
    "            transition_matrix[1][0, 1] -= phi            \n",
    "\n",
    "            \n",
    "        \n",
    "        a = -transition_matrix[0][0,1] + transition_matrix[0][1,1] - transition_matrix[1][0,0] + transition_matrix[1][1,0]\n",
    "        \n",
    "        #The value of a allows to understand how the phase space is organized\n",
    "        \n",
    "        print(f'alpha={alpha}', f'beta={beta}', f'psi={psi}', f'phi={phi}', a>0)\n",
    "        \n",
    "        #-p_1,1,2+p_1,2,2-p_2,1,1+p_2,2,1\n",
    "\n",
    "        transition_matrix[0] = transition_matrix[0].T\n",
    "        transition_matrix[1] = transition_matrix[1].T\n",
    "\n",
    "        transition_matrix_T = [transition_matrix[i].T for i in range(len(transition_matrix))]\n",
    "        y=symbols(f'y1:{m}')\n",
    "        solutions = solve([right_part(y, i, m, transition_matrix_T) for i in range(m-1)], y)\n",
    "        for solution in solutions:\n",
    "            print(round(solution[0], 3), 1 - round(solution[0], 3))\n",
    "            if (solution[0] <= 1) & (0 <= solution[0]):\n",
    "                table_mean_field_approx.append([alpha, beta, phi, psi, solution[0]])\n",
    "        print('\\n')\n",
    "            \n",
    "#table_mean_field_approx = pd.DataFrame(table_mean_field_approx, columns=['alpha', 'psi', 'y1'])\n",
    "\n",
    "#table_mean_field_approx.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "individual-computer",
   "metadata": {},
   "source": [
    "# Scenario 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "interim-supplier",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alpha=0.025 beta=0.003 psi=0.049 phi=0 False\n",
      "0.0 1\n",
      "1.00000000000000 0\n",
      "\n",
      "\n",
      "alpha=0.025 beta=0.006 psi=0.049 phi=0 False\n",
      "0.0 1\n",
      "1.00000000000000 0\n",
      "\n",
      "\n",
      "alpha=0.025 beta=0.009 psi=0.049 phi=0 False\n",
      "0.0 1\n",
      "1.00000000000000 0\n",
      "\n",
      "\n",
      "alpha=0.025 beta=0.012 psi=0.049 phi=0 False\n",
      "0.0 1\n",
      "1.00000000000000 0\n",
      "\n",
      "\n",
      "alpha=0.025 beta=0.015 psi=0.049 phi=0 False\n",
      "0.0 1\n",
      "1.00000000000000 0\n",
      "\n",
      "\n",
      "alpha=0.025 beta=0.018 psi=0.049 phi=0 False\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "m=2\n",
    "#table_mean_field_approx = []\n",
    "#phi = 0\n",
    "alpha = 0.025\n",
    "psi = 0.049\n",
    "for beta in [0.003, 0.006, 0.009, 0.012, 0.015, 0.018]:\n",
    "    for phi in [0]:\n",
    "    #for psi in [0, 0.01, 0.02, 0.03, 0.04, 0.048, 0.049]:\n",
    "\n",
    "        #load transition matrix\n",
    "        transition_matrix = []\n",
    "        for i in range(m):\n",
    "            transition_matrix.append(np.load(f'Transition matrices/Matrix_{m}_{i+1}.npy'))\n",
    "            #transition_matrix.append(np.load(f'Transition matrices/Matrix_{m}_{i+1}_second_iteration.npy'))\n",
    "\n",
    "        transition_matrix[0] = transition_matrix[0].T\n",
    "        transition_matrix[1] = transition_matrix[1].T\n",
    "\n",
    "        if alpha != 0.025:\n",
    "            transition_matrix[0][0, 0] += alpha\n",
    "            transition_matrix[0][0, 1] -= alpha\n",
    "        else:\n",
    "            transition_matrix[0][0, 0] = 1\n",
    "            transition_matrix[0][0, 1] = 0\n",
    "\n",
    "        if psi != 0.049:\n",
    "            transition_matrix[1][1, 0] -= psi\n",
    "            transition_matrix[1][1, 1] += psi\n",
    "        else:\n",
    "            transition_matrix[1][1, 0] = 0\n",
    "            transition_matrix[1][1, 1] = 1                       \n",
    "        \n",
    "        \n",
    "        if (phi == 0) & (beta == 0.018):\n",
    "            transition_matrix[0][1, 0] = transition_matrix[1][0, 1]\n",
    "            transition_matrix[0][1, 1] = transition_matrix[1][0, 0]\n",
    "        else:\n",
    "            transition_matrix[0][1, 0] -= beta\n",
    "            transition_matrix[0][1, 1] += beta\n",
    "            transition_matrix[1][0, 0] += phi\n",
    "            transition_matrix[1][0, 1] -= phi  \n",
    "            \n",
    "        \n",
    "        a = -transition_matrix[0][0,1] + transition_matrix[0][1,1] - transition_matrix[1][0,0] + transition_matrix[1][1,0]\n",
    "        \n",
    "        print(f'alpha={alpha}', f'beta={beta}', f'psi={psi}', f'phi={phi}', a>0)\n",
    "        \n",
    "        #-p_1,1,2+p_1,2,2-p_2,1,1+p_2,2,1\n",
    "\n",
    "        transition_matrix[0] = transition_matrix[0].T\n",
    "        transition_matrix[1] = transition_matrix[1].T\n",
    "\n",
    "        transition_matrix_T = [transition_matrix[i].T for i in range(len(transition_matrix))]\n",
    "        y=symbols(f'y1:{m}')\n",
    "        solutions = solve([right_part(y, i, m, transition_matrix_T) for i in range(m-1)], y)\n",
    "        for solution in solutions:\n",
    "            print(round(solution[0], 3), 1 - round(solution[0], 3))\n",
    "            if (solution[0] <= 1) & (0 <= solution[0]):\n",
    "                table_mean_field_approx.append([alpha, beta, phi, psi, solution[0]])\n",
    "        print('\\n')\n",
    "            \n",
    "#table_mean_field_approx = pd.DataFrame(table_mean_field_approx, columns=['alpha', 'psi', 'y1'])\n",
    "\n",
    "#table_mean_field_approx.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "grateful-awareness",
   "metadata": {},
   "source": [
    "# Scenario 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "specialized-firewall",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alpha=-0.02 beta=-0.02 psi=-0.02 phi=-0.02 True\n",
      "0.592 0.408\n",
      "21.168 -20.168\n",
      "\n",
      "\n",
      "alpha=-0.02 beta=-0.01 psi=-0.02 phi=-0.01 True\n",
      "0.592 0.408\n",
      "21.168 -20.168\n",
      "\n",
      "\n",
      "alpha=-0.02 beta=0 psi=-0.02 phi=0 True\n",
      "0.592 0.408\n",
      "21.168 -20.168\n",
      "\n",
      "\n",
      "alpha=-0.02 beta=0.01 psi=-0.02 phi=0.01 True\n",
      "0.592 0.408\n",
      "21.168 -20.168\n",
      "\n",
      "\n",
      "alpha=-0.02 beta=0.02 psi=-0.02 phi=0.02 True\n",
      "0.592 0.408\n",
      "21.168 -20.168\n",
      "\n",
      "\n",
      "alpha=-0.01 beta=-0.02 psi=-0.01 phi=-0.02 True\n",
      "0.612 0.388\n",
      "17.502 -16.502\n",
      "\n",
      "\n",
      "alpha=-0.01 beta=-0.01 psi=-0.01 phi=-0.01 True\n",
      "0.612 0.388\n",
      "17.502 -16.502\n",
      "\n",
      "\n",
      "alpha=-0.01 beta=0 psi=-0.01 phi=0 True\n",
      "0.612 0.388\n",
      "17.502 -16.502\n",
      "\n",
      "\n",
      "alpha=-0.01 beta=0.01 psi=-0.01 phi=0.01 True\n",
      "0.612 0.388\n",
      "17.502 -16.502\n",
      "\n",
      "\n",
      "alpha=-0.01 beta=0.02 psi=-0.01 phi=0.02 True\n",
      "0.612 0.388\n",
      "17.502 -16.502\n",
      "\n",
      "\n",
      "alpha=0 beta=-0.02 psi=0 phi=-0.02 True\n",
      "0.643 0.357\n",
      "13.826 -12.826\n",
      "\n",
      "\n",
      "alpha=0 beta=-0.01 psi=0 phi=-0.01 True\n",
      "0.643 0.357\n",
      "13.826 -12.826\n",
      "\n",
      "\n",
      "alpha=0 beta=0 psi=0 phi=0 True\n",
      "0.643 0.357\n",
      "13.826 -12.826\n",
      "\n",
      "\n",
      "alpha=0 beta=0.01 psi=0 phi=0.01 True\n",
      "0.643 0.357\n",
      "13.826 -12.826\n",
      "\n",
      "\n",
      "alpha=0 beta=0.02 psi=0 phi=0.02 True\n",
      "0.643 0.357\n",
      "13.826 -12.826\n",
      "\n",
      "\n",
      "alpha=0.01 beta=-0.02 psi=0.01 phi=-0.02 True\n",
      "0.698 0.302\n",
      "10.125 -9.1250\n",
      "\n",
      "\n",
      "alpha=0.01 beta=-0.01 psi=0.01 phi=-0.01 True\n",
      "0.698 0.302\n",
      "10.125 -9.1250\n",
      "\n",
      "\n",
      "alpha=0.01 beta=0 psi=0.01 phi=0 True\n",
      "0.698 0.302\n",
      "10.125 -9.1250\n",
      "\n",
      "\n",
      "alpha=0.01 beta=0.01 psi=0.01 phi=0.01 True\n",
      "0.698 0.302\n",
      "10.125 -9.1250\n",
      "\n",
      "\n",
      "alpha=0.01 beta=0.02 psi=0.01 phi=0.02 True\n",
      "0.698 0.302\n",
      "10.125 -9.1250\n",
      "\n",
      "\n",
      "alpha=0.02 beta=-0.02 psi=0.02 phi=-0.02 True\n",
      "0.826 0.174\n",
      "6.352 -5.352\n",
      "\n",
      "\n",
      "alpha=0.02 beta=-0.01 psi=0.02 phi=-0.01 True\n",
      "0.826 0.174\n",
      "6.352 -5.352\n",
      "\n",
      "\n",
      "alpha=0.02 beta=0 psi=0.02 phi=0 True\n",
      "0.826 0.174\n",
      "6.352 -5.352\n",
      "\n",
      "\n",
      "alpha=0.02 beta=0.01 psi=0.02 phi=0.01 True\n",
      "0.826 0.174\n",
      "6.352 -5.352\n",
      "\n",
      "\n",
      "alpha=0.02 beta=0.02 psi=0.02 phi=0.02 True\n",
      "0.826 0.174\n",
      "6.352 -5.352\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "m=2\n",
    "\n",
    "for alpha in [-0.02, -0.01, 0, 0.01, 0.02]:\n",
    "    for beta in [-0.02, -0.01, 0, 0.01, 0.02]:\n",
    "                    \n",
    "        #load transition matrix\n",
    "        transition_matrix = []\n",
    "        for i in range(m):\n",
    "            transition_matrix.append(np.load(f'Transition matrices/Matrix_{m}_{i+1}.npy'))\n",
    "            #transition_matrix.append(np.load(f'Transition matrices/Matrix_{m}_{i+1}_second_iteration.npy'))\n",
    "\n",
    "        transition_matrix[0] = transition_matrix[0].T\n",
    "        transition_matrix[1] = transition_matrix[1].T\n",
    "                    \n",
    "        psi = alpha\n",
    "        phi = beta\n",
    "\n",
    "        transition_matrix[0][0, 0] += alpha\n",
    "        transition_matrix[0][0, 1] -= alpha\n",
    "        transition_matrix[1][1, 0] -= psi\n",
    "        transition_matrix[1][1, 1] += psi\n",
    "\n",
    "        transition_matrix[0][1, 0] -= beta\n",
    "        transition_matrix[0][1, 1] += beta\n",
    "        transition_matrix[1][0, 0] += phi\n",
    "        transition_matrix[1][0, 1] -= phi            \n",
    "\n",
    "        a = -transition_matrix[0][0,1] + transition_matrix[0][1,1] - transition_matrix[1][0,0] + transition_matrix[1][1,0]\n",
    "        \n",
    "        print(f'alpha={alpha}', f'beta={beta}', f'psi={psi}', f'phi={phi}', a>0)\n",
    "        \n",
    "        #-p_1,1,2+p_1,2,2-p_2,1,1+p_2,2,1\n",
    "\n",
    "        transition_matrix[0] = transition_matrix[0].T\n",
    "        transition_matrix[1] = transition_matrix[1].T\n",
    "\n",
    "        transition_matrix_T = [transition_matrix[i].T for i in range(len(transition_matrix))]\n",
    "        y=symbols(f'y1:{m}')\n",
    "        solutions = solve([right_part(y, i, m, transition_matrix_T) for i in range(m-1)], y)\n",
    "        for solution in solutions:\n",
    "            print(round(solution[0], 3), 1 - round(solution[0], 3))\n",
    "            if (solution[0] <= 1) & (0 <= solution[0]):\n",
    "                table_mean_field_approx.append([alpha, beta, phi, psi, solution[0]])\n",
    "        print('\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ahead-catalog",
   "metadata": {},
   "source": [
    "# Create Pandas table with mean-field predictions for given values of the error parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "assisted-democracy",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>alpha</th>\n",
       "      <th>beta</th>\n",
       "      <th>phi</th>\n",
       "      <th>psi</th>\n",
       "      <th>y1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.642963838036734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.623381150849412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.598546502583694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.564900495500786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.513158446607635</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   alpha  beta  phi   psi                 y1\n",
       "0    0.0   0.0  0.0  0.00  0.642963838036734\n",
       "1    0.0   0.0  0.0  0.01  0.623381150849412\n",
       "2    0.0   0.0  0.0  0.02  0.598546502583694\n",
       "3    0.0   0.0  0.0  0.03  0.564900495500786\n",
       "4    0.0   0.0  0.0  0.04  0.513158446607635"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table_mean_field_approx = pd.DataFrame(table_mean_field_approx, columns=['alpha', 'beta', 'phi', 'psi', 'y1'])\n",
    "\n",
    "table_mean_field_approx.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "flying-craft",
   "metadata": {},
   "source": [
    "# Vizualize single experiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "minor-playing",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0 1.0\n",
      "0.41957285758380064 0.5804271424161993\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 936x936 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "N, T, topology_id = 2000, 500000, 'random_geom'\n",
    "\n",
    "#N = 2000\n",
    "#T = 500000\n",
    "#topology_id = 'random_geom'\n",
    "\n",
    "t_freq = 25000\n",
    "\n",
    "m = 2\n",
    "possible_ops = np.array([-1, 1])\n",
    "th_value = 0\n",
    "\n",
    "\n",
    "selectivity_rate = -0.01  #no selectivity\n",
    "pers_rate = -0.01  #no personalization\n",
    "\n",
    "#beta = 0.015\n",
    "#phi = 0\n",
    "#alpha = 0.025\n",
    "#psi = 0.049\n",
    "\n",
    "beta = 0\n",
    "phi = 0\n",
    "alpha = 0\n",
    "psi = 0.049\n",
    "\n",
    "in_ops_type = ('uniform', )\n",
    "#in_ops_type = ('manual', [0.1, 0.9])\n",
    "\n",
    "main_folder = 'New_experiments_noise'\n",
    "\n",
    "counter = 2\n",
    "\n",
    "pos, Ops, public_opinion, pols, assrts, components_number, A_0, A, t_measurements = load_noise(main_folder, \n",
    "                                                                                               N, \n",
    "                                                                                               m, \n",
    "                                                                                               in_ops_type, \n",
    "                                                                                               topology_id, \n",
    "                                                                                               selectivity_rate, \n",
    "                                                                                               pers_rate, \n",
    "                                                                                               th_value, \n",
    "                                                                                               t_freq, \n",
    "                                                                                               T, \n",
    "                                                                                               alpha, \n",
    "                                                                                               beta, \n",
    "                                                                                               phi, \n",
    "                                                                                               psi, \n",
    "                                                                                               counter)\n",
    "\n",
    "\n",
    "#load transition matrix\n",
    "transition_matrix = []\n",
    "for i in range(m):\n",
    "    transition_matrix.append(np.load(f'Transition matrices/Matrix_{m}_{i+1}.npy'))\n",
    "    #transition_matrix.append(np.load(f'Transition matrices/Matrix_{m}_{i+1}_second_iteration.npy'))\n",
    "    \n",
    "transition_matrix[0] = transition_matrix[0].T\n",
    "transition_matrix[1] = transition_matrix[1].T\n",
    "                    \n",
    "if alpha != 0.025:\n",
    "    transition_matrix[0][0, 0] += alpha\n",
    "    transition_matrix[0][0, 1] -= alpha\n",
    "else:\n",
    "    transition_matrix[0][0, 0] = 1\n",
    "    transition_matrix[0][0, 1] = 0\n",
    "                    \n",
    "#transition_matrix[0][1, 0] -= beta\n",
    "#transition_matrix[0][1, 1] += beta\n",
    "\n",
    "#transition_matrix[1][0, 0] += beta\n",
    "#transition_matrix[1][0, 1] -= beta\n",
    "                    \n",
    "if psi != 0.049:\n",
    "    transition_matrix[1][1, 0] -= psi\n",
    "    transition_matrix[1][1, 1] += psi\n",
    "else:\n",
    "    transition_matrix[1][1, 0] = 0\n",
    "    transition_matrix[1][1, 1] = 1                       \n",
    "\n",
    "\n",
    "transition_matrix[0] = transition_matrix[0].T\n",
    "transition_matrix[1] = transition_matrix[1].T\n",
    "\n",
    "transition_matrix_T = [transition_matrix[i].T for i in range(len(transition_matrix))]\n",
    "\n",
    "y=symbols(f'y1:{m}')\n",
    "\n",
    "solutions = solve([right_part(y, i, m, transition_matrix_T) for i in range(m-1)], y)\n",
    "\n",
    "fig = plt.figure(figsize=(13, 13))\n",
    "sub = fig.add_subplot(1, 1, 1) # 3 rows, 2 columns, 1 cell\n",
    "#sub.set_title('A', fontsize=50, loc='left')\n",
    "\n",
    "\n",
    "sub.plot(np.arange(T+1), np.array(public_opinion[0])/N, color='lightcoral', \n",
    "         label='$y_{1}(t)$', \n",
    "         linestyle='-', linewidth=5)\n",
    "\n",
    "sub.plot(np.arange(T+1), np.array(public_opinion[1])/N, color='lightsteelblue', \n",
    "         label='$y_{2}(t)$', \n",
    "         linestyle='-', linewidth=5)\n",
    "\n",
    "#sub.plot(t_measurements, pols, color='black', \n",
    "#         label='polarization', \n",
    "#         linestyle='-.', linewidth=5)\n",
    "\n",
    "#sub.plot(t_measurements, assrts, color='darkgreen', \n",
    "#         label='assortativity', \n",
    "#         linestyle='-.', linewidth=5)\n",
    "\n",
    "sub.set_xlabel('$t$', fontsize=40)\n",
    "\n",
    "#Mean-field predictions (applicable only for Model 1!!!)\n",
    "\n",
    "if solutions:\n",
    "\n",
    "    for i in solutions:\n",
    "\n",
    "        #print(round(i[0], 3), 1-round(i[0], 3), type(round(i[0], 3)))\n",
    "        \n",
    "        a = float(i[0])\n",
    "        b = float(1-i[0])\n",
    "        \n",
    "        print(a, b)\n",
    "        \n",
    "        sub.hlines(y=a, xmin=0, xmax=T, ls='--', lw=5, color='r')\n",
    "        sub.hlines(y=b, xmin=0, xmax=T, ls='--', lw=5, color='b')\n",
    "\n",
    "sub.set_xlim([0, T])\n",
    "sub.set_ylim([-0.05, 1.05])\n",
    "\n",
    "sub.tick_params(axis='both', labelsize=25)\n",
    "sub.legend(fontsize=40, loc='center right')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "final-brook",
   "metadata": {},
   "source": [
    "# Plot how errors in transition matrix (2) from Main Manuscript affect behavior of the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "cardiac-playlist",
   "metadata": {},
   "outputs": [],
   "source": [
    "def prepare_table_with_result_scenario_1(N, m, x, in_ops_type, topology_id, selectivity_rate, pers_rate, th_value, t_freq, T, n_exp=7):\n",
    "    \n",
    "    #prepare table for storing experiments\n",
    "    \n",
    "    phi = 0\n",
    "    beta = 0\n",
    "    \n",
    "    results = []\n",
    "    for counter in np.arange(1, n_exp+1):\n",
    "        for alpha in x:\n",
    "            for psi in [0, 0.01, 0.02, 0.03, 0.04, 0.049]:\n",
    "                \n",
    "                try:\n",
    "                \n",
    "                    pos, Ops, public_opinion, pols, assrts, components_number, A_0, A, t_measurements = load_noise(main_folder, \n",
    "                                                                                                           N, \n",
    "                                                                                                           m, \n",
    "                                                                                                           in_ops_type, \n",
    "                                                                                                           topology_id, \n",
    "                                                                                                           selectivity_rate, \n",
    "                                                                                                           pers_rate, \n",
    "                                                                                                           th_value, \n",
    "                                                                                                           t_freq, \n",
    "                                                                                                           T, \n",
    "                                                                                                           alpha, \n",
    "                                                                                                           beta, \n",
    "                                                                                                           phi, \n",
    "                                                                                                           psi, \n",
    "                                                                                                           counter)\n",
    "\n",
    "                    results.append([alpha, beta, phi, psi, public_opinion[0][-1], assrts.max()])\n",
    "                    \n",
    "                except Exception as exception:\n",
    "                    \n",
    "                    pass\n",
    "\n",
    "    results = pd.DataFrame(results, columns=['alpha', 'beta', 'phi', 'psi', 'Y1', 'assrt'])    \n",
    "    \n",
    "    return results\n",
    "\n",
    "\n",
    "def prepare_table_with_result_scenario_2(N, m, x, in_ops_type, topology_id, selectivity_rate, pers_rate, th_value, t_freq, T, n_exp=7):\n",
    "    \n",
    "    #prepare table for storing experiments\n",
    "    \n",
    "    alpha = 0.025\n",
    "    psi = 0.049\n",
    "    \n",
    "    results = []\n",
    "    for counter in np.arange(1, n_exp+1):\n",
    "        for beta in x:\n",
    "            for phi in [0]:\n",
    "                try:\n",
    "                \n",
    "                    pos, Ops, public_opinion, pols, assrts, components_number, A_0, A, t_measurements = load_noise(main_folder, \n",
    "                                                                                                           N, \n",
    "                                                                                                           m, \n",
    "                                                                                                           in_ops_type, \n",
    "                                                                                                           topology_id, \n",
    "                                                                                                           selectivity_rate, \n",
    "                                                                                                           pers_rate, \n",
    "                                                                                                           th_value, \n",
    "                                                                                                           t_freq, \n",
    "                                                                                                           T, \n",
    "                                                                                                           alpha, \n",
    "                                                                                                           beta, \n",
    "                                                                                                           phi, \n",
    "                                                                                                           psi, \n",
    "                                                                                                           counter)\n",
    "\n",
    "                    results.append([alpha, beta, phi, psi, public_opinion[0][-1], assrts.max()])\n",
    "                    \n",
    "                except Exception as exception:\n",
    "                    \n",
    "                    pass\n",
    "\n",
    "    results = pd.DataFrame(results, columns=['alpha', 'beta', 'phi', 'psi', 'Y1', 'assrt'])    \n",
    "    \n",
    "    return results\n",
    "\n",
    "\n",
    "\n",
    "def prepare_table_with_result_scenario_3(N, m, x, in_ops_type, topology_id, selectivity_rate, pers_rate, th_value, t_freq, T, n_exp=7):\n",
    "    \n",
    "    #prepare table for storing experiments\n",
    "    \n",
    "\n",
    "    \n",
    "    results = []\n",
    "    for counter in np.arange(1, n_exp+1):\n",
    "        for alpha in x:\n",
    "            for beta in [-0.02, -0.01, 0, 0.01, 0.02]:\n",
    "                \n",
    "                psi = alpha\n",
    "                phi = beta\n",
    "                \n",
    "                try:\n",
    "                \n",
    "                    pos, Ops, public_opinion, pols, assrts, components_number, A_0, A, t_measurements = load_noise(main_folder, \n",
    "                                                                                                           N, \n",
    "                                                                                                           m, \n",
    "                                                                                                           in_ops_type, \n",
    "                                                                                                           topology_id, \n",
    "                                                                                                           selectivity_rate, \n",
    "                                                                                                           pers_rate, \n",
    "                                                                                                           th_value, \n",
    "                                                                                                           t_freq, \n",
    "                                                                                                           T, \n",
    "                                                                                                           alpha, \n",
    "                                                                                                           beta, \n",
    "                                                                                                           phi, \n",
    "                                                                                                           psi, \n",
    "                                                                                                           counter)\n",
    "\n",
    "                    results.append([alpha, beta, phi, psi, public_opinion[0][-1], assrts.max()])\n",
    "                    \n",
    "                except Exception as exception:\n",
    "                    \n",
    "                    pass\n",
    "\n",
    "\n",
    "    results = pd.DataFrame(results, columns=['alpha', 'beta', 'phi', 'psi', 'Y1', 'assrt'])    \n",
    "    \n",
    "    return results\n",
    "\n",
    "def plot_scenario_1_public_op(N, results, table_mean_field_approx, sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size):\n",
    "    \n",
    "    mask = (results['psi'] == psi) & (results['beta'] == beta) & (results['phi'] == phi) & (results['alpha'].isin(x))\n",
    "    data_sample = results[mask]\n",
    "    sub.scatter(data_sample['alpha'], data_sample['Y1']/N, \n",
    "                #mec='k', mew=2,\n",
    "                marker='o', s=marker_size, \n",
    "                color='white', \n",
    "                linewidths=3, edgecolors=color_, #alpha=1, \n",
    "                label=r'$\\psi=$'+f'{psi}', \n",
    "               )\n",
    "    \n",
    "    mask = (table_mean_field_approx['psi'] == psi) & (table_mean_field_approx['beta'] == beta) & (table_mean_field_approx['phi'] == phi) & (table_mean_field_approx['alpha'].isin(x))\n",
    "    table_mean_field_approx_sample = table_mean_field_approx[mask]\n",
    "    sub.scatter(table_mean_field_approx_sample['alpha'], \n",
    "                table_mean_field_approx_sample['y1'], \n",
    "                #mec='k', mew=2,\n",
    "                marker='s', s=mean_field_marker_size, \n",
    "                color=color_, \n",
    "                linewidths=3, edgecolors='k', #alpha=1, \n",
    "                #label=r'$\\psi=$'+f'{psi}', \n",
    "                zorder=3,\n",
    "               )\n",
    "\n",
    "\n",
    "    return 0\n",
    "\n",
    "def plot_scenario_2_public_op(N, results, table_mean_field_approx, sub, x, alpha, psi, phi, color_, marker_size, mean_field_marker_size):\n",
    "    \n",
    "    mask = (results['psi'] == psi) & (results['alpha'] == alpha) & (results['phi'] == phi) & (results['beta'].isin(x))\n",
    "    data_sample = results[mask]\n",
    "    sub.scatter(data_sample['beta'], data_sample['Y1']/N, \n",
    "                #mec='k', mew=2,\n",
    "                marker='o', s=marker_size, \n",
    "                color='white', \n",
    "                linewidths=3, edgecolors=color_, #alpha=1, \n",
    "                #label=r'$\\psi=$'+f'{psi}', \n",
    "               )\n",
    "    \n",
    "    #print(data_sample)\n",
    "    \n",
    "    mask = (table_mean_field_approx['psi'] == psi) & (table_mean_field_approx['alpha'] == alpha) & (table_mean_field_approx['phi'] == phi) & (table_mean_field_approx['beta'].isin(x))\n",
    "    table_mean_field_approx_sample = table_mean_field_approx[mask]\n",
    "    sub.scatter(table_mean_field_approx_sample['beta'], \n",
    "                table_mean_field_approx_sample['y1'], \n",
    "                #mec='k', mew=2,\n",
    "                marker='s', s=mean_field_marker_size, \n",
    "                color=color_, \n",
    "                linewidths=3, edgecolors='k', #alpha=1, \n",
    "                #label=r'$\\psi=$'+f'{psi}', \n",
    "                zorder=3,\n",
    "               )\n",
    "\n",
    "\n",
    "    return 0\n",
    "    \n",
    "\n",
    "    \n",
    "def plot_scenario_3_public_op(N, results, table_mean_field_approx, sub, x, beta, color_, marker_size, mean_field_marker_size):\n",
    "    \n",
    "    \n",
    "    mask = (results['beta'] == beta) & (results['psi'] == results['alpha']) & (results['phi'] == results['beta']) & (results['alpha'].isin(x))\n",
    "    data_sample = results[mask]\n",
    "    sub.scatter(data_sample['alpha'], data_sample['Y1']/N, \n",
    "                #mec='k', mew=2,\n",
    "                marker='o', s=marker_size, \n",
    "                color='white', \n",
    "                linewidths=3, edgecolors=color_, #alpha=1, \n",
    "                label=r'$\\beta=$'+f'{beta}', \n",
    "               )\n",
    "    \n",
    "    \n",
    "    \n",
    "    mask = (table_mean_field_approx['beta'] == beta) & (table_mean_field_approx['psi'] == table_mean_field_approx['alpha']) & (table_mean_field_approx['phi'] == table_mean_field_approx['beta']) & (table_mean_field_approx['alpha'].isin(x))\n",
    "    table_mean_field_approx_sample = table_mean_field_approx[mask]\n",
    "    sub.scatter(table_mean_field_approx_sample['alpha'], \n",
    "                table_mean_field_approx_sample['y1'], \n",
    "                #mec='k', mew=2,\n",
    "                marker='s', s=mean_field_marker_size, \n",
    "                color=color_, \n",
    "                linewidths=3, edgecolors='k', #alpha=1, \n",
    "                #label=r'$\\psi=$'+f'{psi}', \n",
    "                zorder=3,\n",
    "               )\n",
    "    #print(data_sample.shape, table_mean_field_approx_sample.shape)\n",
    "\n",
    "    return 0\n",
    "\n",
    "\n",
    "def plot_scenaio_1_assrt(N, results, table_mean_field_approx, sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size):\n",
    "    \n",
    "    mask = (results['psi'] == psi) & (results['beta'] == beta) & (results['phi'] == phi) & (results['alpha'].isin(x))\n",
    "    data_sample = results[mask]\n",
    "    sub.scatter(data_sample['alpha'], data_sample['assrt'], \n",
    "                #mec='k', mew=2,\n",
    "                marker='o', s=marker_size, \n",
    "                color='white', \n",
    "                linewidths=3, edgecolors=color_, #alpha=1, \n",
    "                label=r'$\\psi=$'+f'{psi}', \n",
    "               )\n",
    "\n",
    "\n",
    "\n",
    "    return 0\n",
    "\n",
    "def plot_scenaio_2_assrt(N, results, table_mean_field_approx, sub, x, alpha, psi, phi, color_, marker_size, mean_field_marker_size):\n",
    "    \n",
    "    mask = (results['psi'] == psi) & (results['alpha'] == alpha) & (results['phi'] == phi) & (results['beta'].isin(x))\n",
    "    data_sample = results[mask]\n",
    "    sub.scatter(data_sample['beta'], data_sample['assrt'], \n",
    "                #mec='k', mew=2,\n",
    "                marker='o', s=marker_size, \n",
    "                color='white', \n",
    "                linewidths=3, edgecolors=color_, #alpha=1, \n",
    "                #label=r'$\\psi=$'+f'{psi}', \n",
    "               )\n",
    "\n",
    "\n",
    "\n",
    "    return 0\n",
    "\n",
    "\n",
    "def plot_scenaio_3_assrt(N, results, table_mean_field_approx, sub, x, beta, color_, marker_size, mean_field_marker_size):\n",
    "    \n",
    "    \n",
    "    psi = alpha\n",
    "    phi = beta\n",
    "    \n",
    "    mask = (results['psi'] == results['alpha']) & (results['beta'] == results['phi']) & (results['beta'] == beta) & (results['alpha'].isin(x))\n",
    "    data_sample = results[mask]\n",
    "    sub.scatter(data_sample['alpha'], data_sample['assrt'], \n",
    "                #mec='k', mew=2,\n",
    "                marker='o', s=marker_size, \n",
    "                color='white', \n",
    "                linewidths=3, edgecolors=color_, #alpha=1, \n",
    "                label=r'$\\beta=$'+f'{beta}', \n",
    "               )\n",
    "\n",
    "\n",
    "\n",
    "    return 0"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "residential-zealand",
   "metadata": {},
   "source": [
    "# Plot the effect of errors on limiting values of public opinion variables in Scenarios 1, 2 on random geometric networks (Figure 3 from Main Manuscript) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "domestic-nicholas",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1872x936 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(26, 13))\n",
    "\n",
    "marker_size = 500\n",
    "mean_field_marker_size = 100\n",
    "\n",
    "x_label_size = 40\n",
    "tick_size = 20\n",
    "legend_size = 25\n",
    "title_size = 35\n",
    "\n",
    "n_rows = 1\n",
    "n_cols = 2\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 1000000, 'random_geom'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "beta = 0\n",
    "phi = 0\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.005, 0.01, 0.015, 0.02, 0.025]\n",
    "results = prepare_table_with_result_scenario_1(N, \n",
    "                                                m, x,\n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 1)\n",
    "sub.set_title('A', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "psi = 0\n",
    "color_ = 'k'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.04\n",
    "color_ = 'darkviolet'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.049\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "sub.set_xlabel(r'$\\alpha$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_1$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "sub.legend(fontsize=legend_size)\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 1000000, 'random_geom'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "alpha = 0.025\n",
    "psi = 0.049\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.003, 0.006, 0.009, 0.012, 0.015, 0.018]\n",
    "results = prepare_table_with_result_scenario_2(N, \n",
    "                                                m, x, \n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 2)\n",
    "sub.set_title('B', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "phi = 0\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_2_public_op(N, \n",
    "                              results, \n",
    "                              table_mean_field_approx, \n",
    "                              sub, x, alpha, psi, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "\n",
    "sub.set_xlabel(r'$\\beta$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_{1}$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "#sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aggressive-reader",
   "metadata": {},
   "source": [
    "# ... Vary the number of agents and initial conditions "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "mineral-channels",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1872x2808 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(26, 39))\n",
    "\n",
    "marker_size = 500\n",
    "mean_field_marker_size = 100\n",
    "\n",
    "x_label_size = 40\n",
    "tick_size = 20\n",
    "legend_size = 25\n",
    "title_size = 35\n",
    "\n",
    "n_rows = 3\n",
    "n_cols = 2\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 1000000, 'random_geom'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "beta = 0\n",
    "phi = 0\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.005, 0.01, 0.015, 0.02, 0.025]\n",
    "results = prepare_table_with_result_scenario_1(N, \n",
    "                                                m, x,\n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 1)\n",
    "sub.set_title(f'A, {N} agents, {T} iterations', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "psi = 0\n",
    "color_ = 'k'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.04\n",
    "color_ = 'darkviolet'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.049\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "sub.set_xlabel(r'$\\alpha$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_1$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "sub.legend(fontsize=legend_size)\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 1000000, 'random_geom'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "alpha = 0.025\n",
    "psi = 0.049\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.003, 0.006, 0.009, 0.012, 0.015, 0.018]\n",
    "results = prepare_table_with_result_scenario_2(N, \n",
    "                                                m, x, \n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 2)\n",
    "sub.set_title(f'B, {N} agents, {T} iterations', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "phi = 0\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_2_public_op(N, \n",
    "                              results, \n",
    "                              table_mean_field_approx, \n",
    "                              sub, x, alpha, psi, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "\n",
    "sub.set_xlabel(r'$\\beta$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_{1}$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "#sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 50, 100000, 'random_geom_50'\n",
    "t_freq = 25000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "beta = 0\n",
    "psi = 0\n",
    "in_ops_type = ('manual', [0.1, 0.9])\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.005, 0.01, 0.015, 0.02, 0.025]\n",
    "results = prepare_table_with_result_scenario_1(N, \n",
    "                                                m, x, \n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 3)\n",
    "sub.set_title(f'C, {N} agents, {T} iterations', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "psi = 0\n",
    "color_ = 'k'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.04\n",
    "color_ = 'darkviolet'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.049\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "sub.set_xlabel(r'$\\alpha$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_{1}$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 50, 100000, 'random_geom_50'\n",
    "t_freq = 25000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "alpha = 0.025\n",
    "psi = 0.049\n",
    "in_ops_type = ('manual', [0.1, 0.9])\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.003, 0.006, 0.009, 0.012, 0.015, 0.018]\n",
    "results = prepare_table_with_result_scenario_2(N, \n",
    "                                                m, x,\n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 4)\n",
    "sub.set_title(f'D, {N} agents, {T} iterations', fontsize=title_size, loc='left')\n",
    "\n",
    "phi = 0\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_2_public_op(N, \n",
    "                              results, \n",
    "                              table_mean_field_approx, \n",
    "                              sub, x, alpha, psi, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "\n",
    "sub.set_xlabel(r'$\\beta$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_{1}$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "#sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 50, 1000000, 'random_geom_50'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "beta = 0\n",
    "psi = 0\n",
    "in_ops_type = ('manual', [0.1, 0.9])\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.005, 0.01, 0.015, 0.02, 0.025]\n",
    "results = prepare_table_with_result_scenario_1(N, \n",
    "                                                m, x,\n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 5)\n",
    "sub.set_title(f'E, {N} agents, {T} iterations', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "psi = 0\n",
    "color_ = 'k'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.04\n",
    "color_ = 'darkviolet'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.049\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "sub.set_xlabel(r'$\\alpha$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_{1}$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 50, 1000000, 'random_geom_50'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "alpha = 0.025\n",
    "psi = 0.049\n",
    "in_ops_type = ('manual', [0.1, 0.9])\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.003, 0.006, 0.009, 0.012, 0.015, 0.018]\n",
    "results = prepare_table_with_result_scenario_2(N, \n",
    "                                                m, x,\n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 6)\n",
    "sub.set_title(f'F, {N} agents, {T} iterations', fontsize=title_size, loc='left')\n",
    "\n",
    "phi = 0\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_2_public_op(N, \n",
    "                              results, \n",
    "                              table_mean_field_approx, \n",
    "                              sub, x, alpha, psi, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "\n",
    "sub.set_xlabel(r'$\\beta$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_{1}$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "#sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "forty-contrary",
   "metadata": {},
   "source": [
    "# ... on WS1 networks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "frozen-qatar",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1872x2808 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(26, 39))\n",
    "\n",
    "marker_size = 500\n",
    "mean_field_marker_size = 100\n",
    "\n",
    "x_label_size = 40\n",
    "tick_size = 20\n",
    "legend_size = 25\n",
    "title_size = 35\n",
    "\n",
    "n_rows = 3\n",
    "n_cols = 2\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 1000000, 'WS1'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "beta = 0\n",
    "phi = 0\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.005, 0.01, 0.015, 0.02, 0.025]\n",
    "results = prepare_table_with_result_scenario_1(N, \n",
    "                                                m, x,\n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 1)\n",
    "sub.set_title('A', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "psi = 0\n",
    "color_ = 'k'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.04\n",
    "color_ = 'darkviolet'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.049\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "sub.set_xlabel(r'$\\alpha$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_1$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "sub.legend(fontsize=legend_size)\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "#\"\"\"\n",
    "\n",
    "N, T, topology_id = 2000, 1000000, 'complete'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "alpha = 0.025\n",
    "psi = 0.049\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.003, 0.006, 0.009, 0.012, 0.015, 0.018]\n",
    "results = prepare_table_with_result_scenario_2(N, \n",
    "                                                m, x, \n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 2)\n",
    "sub.set_title('B', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "phi = 0\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_2_public_op(N, \n",
    "                              results, \n",
    "                              table_mean_field_approx, \n",
    "                              sub, x, alpha, psi, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "\n",
    "sub.set_xlabel(r'$\\beta$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_{1}$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "#sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "#\"\"\"\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "mental-lease",
   "metadata": {},
   "source": [
    "# ... on Erdős–Rényi networks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "occupied-hughes",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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R0tLi9/sPQJId1jcPfpzxYvNEcDV496P9etiy4eGIPr4KwKvr4a2ngprt34TWzsjDpCVDS6iJBB9ZB5/S8jcRO/0b2B48wyZqr0fpQZhxx8DHJwAD//dKhoReD+lNvC1D9LdAHpAO/I9BxPl3rDfy60zTLDFN81HTNO8Evg/cAIyZuYP19fWsWLGC2bNns2nTJqqqqoJmErhcLqqqqti0aROzZ8/m3nvvpb5eTwyJiIjI6OWXKJhVbC3hMRiOIpi1FLBmF0xIUyHLMWJsfr7wTRT4/P7358aCX3+f3/+g+NI330TBULwevvGlb29tDtncnxvTvfYPE1/C+M3XQzZH7fUIE1/6obV+YP9eteq+0lAZ8P8fEteSRnoAQ8E0zQPu7YE8FdZzXi6wBDgJ/N+Aw98CVgN/YRjGI6ZpXh7YSGPD9u3bWbt2LY2NjUHHHA4H6enpNDc3U1dX52k3TZOdO3eyf/9+tmzZQmlp6TCOOP60tLTwxBNPUF5ejtPpJDExkby8PFauXMnDDz+MzWYb6SGKiIiMfvlrQjab3wt/ivH3YeKc3BudMUlMiIvPF/r9jy16PWJAiFUYphYCh7w9In09phbCB4cCeoy9VR6G1LnDfXbp998Pv/hv9Ws4EuC97bB/rV9TxK/HM/Ng8Ra4UfeVhtKg/n5IXBmrMwui4c6e76+Yptnte8A0zRbgdSAV+NhwDyyaNm/ezMqVK/0SBcXFxezatYuGhgZOnTrF0aNHOXXqFA0NDezatYvi4mJP38bGRlauXMnmzXoqYqjU1taSn5/Pt7/9bY4ePYppmnR2dvLmm2/y93//93zsYx/j0iWtiSwiItJfv3roIf+GSAuI9mWGf5yg60i8iq3PF9Vb/PeH6Pc/6DoSWs0z/vtD9XoEXkdCa/hjcFtPDYkBCawh0dt1JJirFbpCTAkILOQdqVDndXVY15H+q94ML6+EzsaBnd/ZaJ1frftKIrFAyYLwbuj5fizM8eM93/OGYSxDYvv27axbt86zn5ubS2VlJbt376akpISsLP8aa1lZWZSUlLB7924OHDjgV7Ng3bp1bN++fdjGHi+6urq45557OHnyJFOnTmXfvn1cvnyZtrY2XnjhBex2O4cPH+a+++4b6aGKiIiMOotznvUuQWR3QEqU6suOz7biYS1FtDjn2ejEldEutj5fVP6Nd3uIfv+DriPh/fqvvdtD+Xr4XkfC++23gtuWlkFK5sDipWRa50dyHQlWHzgrg6FJ3oS6jvTuve1wYF3f/SJxYJ0VT0RGlJIF4WX0fG8Kc9zdnhkugGEYqw3DeNMwjDfPnz8fzbENWn19PWvXeqeIFRYWUlVVxcKFkT3BUlRURHV1NYWF3oz82rVrVcMgyp555hmOHDkCQHl5OYsXLwYgISGB0tJStm7dCsDu3bt59dVXR2ycIiIio1FiUpd3x5Ye3eA2u/c6iV29dJQ4MqjPF1H/bGFe9W4P4e+/33UkvK4O7/ZQvh6+15HwLhz1349yTRvvdd4eXMx40XYuuG0okjftFwYWL1611vsvPWQkDiyO73n716qGgcgIU7Jg4NzPoYVdaNA0zW2maRaYplkwefLkYRpWZNavX+9ZeignJ4eKigoyMzP7FSMzM5OKigrPDIPGxkbWr18f5ZFGx/Tp0zEMg5/+9KeetiNHjmAYBoZh0NTk/cz2ne98B8MwuPXWW0diqH5+8pOfALBo0SK/xIzbypUrPX/+vj+biIiI9K3rqs+HU1dzdIO7vIVdu7oG+OFZ4k2vny+i/tnC8ClfN4S//37XkfD0esSWwOVowtSQ6LfAOFr2JjKNTv/9oUreXDoxuJjx5sB6/6WHzAE+HOF7XmejFVdERoySBeG57x5nhDmeHtBv1HA6nZSXl3v2y8rK+p0ocMvMzKSszJuRdxfgjSXnzp3zzHi45ZZbPO2HD1sFknJzc8nIyAhq9+07Etra2nj99dcBuPvuu0P2MQzDU0PilVdeGbaxiYiIjAX7nX+B6b4t21IHHVGqAdTeYMUDTNO6jgix9vmi6Afe7SH6/Q+6joSX77M80FC+HvlahigiCcn++0NVQyLRFp24Y163/+5QJW8GVr8+PjU54Vh53/0G4li5FV9ERoSSBeH9oed7uDVD5/R8D7fmaMzatm0bZs8n4+LiYoqKigYVr6ioiKVLrYy8aZps27ZtsEOMqqqqKgBSUlKYO3eupz1cUsDdvmDBgmEaYWjvvvsu3d3Wm6Kbb745bD/3sbNnz9LQ0DAsYxMRERkLPvP00/4NdQejE/i0f5yg60i8iq3PFwvW+u8P0e9/0HUktDs2+u8P1esReB0JLcnnJv5Q1pBITA7fV7wuBfyzOFTJm4Y/hO4nwWq2ETQRLmoFp82e+CIyEjQHMbwDPd+XGIaRYJqmJ5VtGIYd+ATQDrwxEoMbjH379nm216yJTkZ+zZo17N27F4D9+/fz2GOPRSVuNLhv/ufn55OUlBTU7pssuHTpEidPngR6TxY888wz/OVf/uWAx3TgwIE+kzS+9R+mT58etp/vsfr6erKzswc8LhERkbhWsxXmlAQ1G38/gDgiwWL784V+/0eWLc1/f6hej8DrSGip18LFnu1eakj0+/UA/xoSadcOIEAc8p3p0Uvypt+vhzt54559k5gysPHFo9p9/vuegtPe1ybi1+PzFfDcAv/ZBLX74fbYua80Fgzo3yuJS3E/s8AwjHGGYdxoGMZs33bTNE8ArwCzgP8ZcNq3gQnAT03TvDwsA40Sl8vlKZgLRFzQuC++cWpqanC5XFGJGw3V1dVA8AyCt956K6jdnUBISkpi/vz5YWOOHz+ea6+9dsBfNlvf001bWrxri6ampobt53vM9xwRERHp2+XW8d6liE7ugbrKwQWsq4ST1gMUpmnFl/gyqj5fJPnctPT5/U9L698NZU//ukrP739QfImAzxooQ/F6aI2VyOUs9m4H1JAY8OvhiefzmW3mp/o7svg03ueBuIDkzaBfD9/kTbRmkIx1XS44X+Pf1lNwekCvR6iC0+f/27qODMqg/35IXBqTyQLDMEoMw3jGMIxngEd7mgvdbYZhfM+n+3TgXeDVEKH+CjgHPGUYxi8Mw3jMMIxfA3+LNT34m0P3UwyN2tpaz418h8NBVlZ0/jPMzs7G4bCmU7pcLmpra6MSNxrcyQLfmQLvv/++p6hxqGTB3LlzSUkJ/1RBaWkpZ8+eHfDXxz/+8aH4UUVERKSf0ja2+TfsXQUdjX5LF0Zi7ty50NFond9bfBmVxuzni/UBhXR7fv83btwY8Q2DtLQ0Nm7cGPL3Pyi+9K600n8/2q9HYHwJb+onvNsBNSQG9Hq4BdaQ8L2OhGf4JLoCkjeDej0goAD4AMcXb5profuKd9+n4PSAX4/AgtPdV6zryKAM+u+HxKWxugzRR4AHAtpye74AaoE+J+CYpnnCMIwC4H8BxcAy4APgKeDbpmmOugXiOzo6PNvp6eGnUw6E3e7NyHd2dkY19kA1NjZ6Ci77JgvcSYFrr72WqVOnBrWPdL0C8P/zbGsLf6PB95jvOSIiIhKZhgtZZE+6ZN2LaHLCi8t4p/q31pNukepohBeXeabQm6YVd+JQDFhGwkcYq58vxk+D9p7lL3t+/x/5nxU88sgjkccI+P33xJX+mXGH/340X49Q8SW8zoC/inUHPctCPfLII/17PXwF1pBwRamQ9VjXdsG77U7e9MwCGNTrEZi8ab8Yvq94Xe3w3/cpFD2o1yN/jf9sqK7YuK80mg3q9ZC4NSZnFpimudE0TaOXr1k+fU8GtgXEqjNN8y9N05xqmqbNNM2ZpmmuH42JAsDvafnm5ug+6eO7BE5ycmwUanIvNRS4rFBfxY0D20fCtGneD1hnzpwJ28/3mO85IiIiEpmJmxq8SxEBfHDIWju3rjKyAHWVVv8PDnmaTNOKK2PDmP588VcB7zOj8PsfMq5E5v4q//1ovR6BcaV/olWLQzU9Bqar3X9/qAqAB15HQjMCbiUOVcFpTfUQGRFjMlkg4c2cOdOzXn5dXR2XLkXnSYaGhgbq6qyMvM1mY+bMmVGJO1jvvfceYP3cvgmMUDMILl68yLvvvgvAJz/5yV7jbt++nSlTpgz467e//W2fY587dy4JCdZf0aNHj4bt5z42ZcoUFTcWEREZoISvmnR3+zQ0OeHni6C8GI7vsp4+9NXeYLWXF1v9fJ7g7e624omMGo8E/L4O4vc/ZDyJ3LUL4JZ1/m2DfT1uWWfFlchl5PjvR7mmjUf6rMHFjBcTHP77Q5W8SXWE7ifh9VJwut/cBadFZESN1WWIJAybzcb8+fOpqrKeLDl48CAlJSWDjnvwoDcjn5+fH1EB3+Fw/vx5wCpI7CvUDIKf/exnmKbJ1KlT+5xZ0N7ezocffjjgcUVSADo1NZVPfOITvPbaa+zZs4evfvWrQX1M02TvXusN55IlSwY8HhEREelJGPyLgWH4LI98cq/35o7dYRVCdLX4L1vQwzStLyUKZFR6xIQnAp7i7Mfvv18cGZw7n4TWM3C83L99IK/HnOVWPOmfrDlYTzX7/D7vXQX3V/dviTq3UDUkMHquI31Kn+6/707e9KyTPyB1lSGSN9ND9ZRAps/TFbboLm/tV3Aa/X8iMhI0syAO3XXXXZ7trVujk5H3jbN48eKoxIwGdwHnY8eOeRIHH374IR988AHgTRY4nU6+/e1vA7Bu3TrPE/3hPPjgg5imOeCvoqKiiMb/wAPW0rgHDhzgd7/7XdDxHTt28P777wPwpS99KaKYIiIiEl7CV00aLmR5bvz7aamDi+8E3Zhz9224kKVEgYxuj5jhaw2E+f33GD9NiYJo+rOdwTMMfPX1eoB1/p/tjP7Y4kGiDVKv9W/rqSFBR2P/YoWrIZF6rXUd6Vva1OC2ngLgAxIyeQPYQ1xHgiV5l7cOLDg9aL4FpxNjY3lrkXijZEEcWr16NUbP43J79uyhsrJyUPEqKys9T7cbhsHq1asHO8SoWbJkCQkJCbhcLpYsWcJrr73Gf/3XfwFWgeeUlBR++MMfctttt3Hx4kVuu+22mCr+8sADDzB//nxM02T58uW8+uqrAHR3d7Njxw6+8pWvAHD33XfzqU99aiSHKiIiMmZM3NSA8fcml1vHexIBgYkD3/bLreMx/t5UjQIZG/7qjHXTP8ned1+w+j1iqkbBULjzSavWQFo/n3ZOm26dpxkFg9NT0NhPtGpIhIsvoSX43jTumQEVteSNz4wqQ8mbiKTPhISePyt3welo8C04nWCzriMiw07JgjiUk5PD8uXLPfurVq2isbFxQLEaGxtZtcqbkV++fDk5OTm9nDG88vLy+Od//mfAKnZ8xx138NnPfhawCjLPmDGDv/qrv+L8+fOUlpbyyiuvMG7cuJEcsp+kpCR++ctfMmvWLM6cOcPixYuZMGECEyZM4Atf+ALNzc3ccsstPP/88yM9VBERkTEnbWMbxt+bGH9v8vK7q+hoH8cVVwId7eN4+d1VnmNpG9tGeqgi0be+2UoCPGLCoh+CkQwkWt8X/dB7bH2UnyoVf9cugDWnofQgTP0YJKWG7peUah0vPWj1V42CwfvTr4VuH2wNib7iSwg+y974Js+ikbxJ851NpdlREUm0weT53v2hKDg9OV8zb0RGiGoWxKknn3yS/fv309jYiNPpZNmyZVRUVJCZmRlxjMbGRpYtW4bTab35yczM5MknY+/plQ0bNrBw4UI2b97Mvn37uHjxoudYXl4eS5cuZdWqVXzkIx8ZuUH2YtasWdTU1PC9732PF198EafTybhx45g3bx5f/OIXefjhh2OmRoSIiMhY9ZmnnwaeBmAc8JkRHY3IMFuw1vqSkTPjDvjznhucrlaoPwRXWmFcGkwrBFvayI5vLMrIgdxPw/sve9uMRDC7rO3+1JDwPQ+suIFFlCW8BJ8H+gwDFj0FB3qW6XInb2Ythfw1MGOhVSjXrb3BugldszW4RsGip+DNf/HuJ8bOg4Mxb8qfwodWLUxqtkZnpoxvwekpBYOPJyIDomRBnJo2bRpbtmxh5cqVABw6dIgFCxZQVlYW0Xr6lZWVrFq1ypMoANiyZQvTpoVZ43SEffzjH+fjH/84YN18r62tpaysjAcffHBkBxYhu93Ot7/9bU9dBRERERERiVO2NJh1V9/9ZPDu2gZPz4GrPTPIzC5rFsfVdvyeQg9bO8KApPHe88E6/65tQzXisck3sdJSBzfdD6nXwL414Gqy2vuTvLFlwF1bYeZd3qQDQPqsIfsRxrShKjgtIiNCyxDFsdLSUp566inPvtPpZNGiRRQXF7Nr1y4aGvynUzY0NLBr1y6Ki4tZtGiRX6LgqaeeorS0dNjGPlBNTU2cOnUKgIICZapFREREREQkjLRpsLTMv+1qG2BaN7AzZ3vXbndLsFntGTlWv6sBS9UtLQtY+kb6lDUHv9oCdQfhxlL4y3cgb4X/MeilALhh9f/Ld6zzfZe9wei5jkTk1AH//WgXnA6MLyLDRjML4tzDDz/MNddcw9q1az11C/bu3espWOxwOLDb7bS0tFBXF5yRz8zMZMuWLaMiUQBw+PBhTNMkJSWFG2+8caSHIyIiIiIiIrHsxlJoO+f/BDr41yKYMKVnxkEbXD4LjSdCx1r0lBVP+ifR1vPne9nady97kzYN7tlhvRY126B2P1yogS6X/7mT8mHmYshf7T9LwXfZm6RUrZEfqS4XXDrm3+YuOP35CkjJjDxWUMHpHpeOWdfRayIy7JQsEEpLS7n99ttZv3495eXlmKZ3OmWoBAGAYRgsX76cJ598MmaXHgqluroagPz8fJKS9OsvIiIiIiIifVjwcM+yN6vBFaKo9+WzvZ9vS7eWHlKiYOCSxnuTBYHL3mTkwO2PWV9dLmiuha5OSEyG9JmhbzjXVfovezNu/JAOf0xpriVkMWh3wemlZd7Xxv16XO2ApBT/16Ou0ppRELIIuGmdp9keIsNOd0sFsGoY7NixA6fTybZt29i/fz81NTW4XN6MvM1mIz8/n8WLF7N69WpyckZfQabDhw8DcMstt4zwSERERERERGTUuLEUZtwOB9bDsZ2Rn5e3AhY9qaWHBqPLFZyk2bsK7q8Ofoo90db3DeZQy950NutJ9ki1N4Q/5i44nZEDJFhLQXX7zPRIsFk1JegOkyTw0XEpGqMVkX5SskD85OTk8Nhjj/HYY4/hcrmora2ls7OT5ORkZs6cic02uv/jfPbZZ3n22WdHehgiIiIiIiIy2oRa9ub8f0P3FW+fhHEw+U9CL3sjA9Nc63PD2QDMKC570xOv26Un2SN18V3//VnFMO9B/5k34RIB3S5oClimyz3z5u3/8J/tceEdmHpr1IYtIpFRskDCstlszJmj/yhFREREREREPAay7I0M3NUO73badGg9bW2HWvamN3WVwcvepE2D1jPWdldnlAY8xo1L8d/PX9PzZ2eE7I7dYSUEXM0hik7jPS9/jX+ywJYajdGKSD8pWSAiIiIiIiIiMhCRLHsjg5Pkc3PaMKxC0e6C0+5lb2YttW42z1gI47O9/dsb4PRBq5ix741osOK8+S/e/cTkofsZxpKkgPoOl/4Arz3q3zar2Ho9HAshJcvb3nEJ6tyvxx6rzdUEL6+ETz7mH0Ovh8iIULJARERERERERERik3u2RpfLejL9pvutgtP710Jno9Xn5F5vMsDuAJsdXC2hn2RPzoTFW2DmXd6kQ6LNuo70zbe2ccpE/0RBRm7PTI+Foc9NyYI5JdZXXaX/TI//b4MVr+Ni8HVEZNgkjPQAREREREREREREQkq0waT53v26g1bB6QfftgpIBy5/01IHF98JkSgwrP4Pvm2df/qg99CkfC0fFakun2WhOn2KEE8thPurwicKAjmKrCLVUwtDx/MtjCwiw0bJAhERERERERERiV0z7/Ju12y1vrsLTn/5BNz6KFxbEHzDP9Fmtd/6qNXvnh3Web5xwCpILZFxFzEGMLut7xk5/S82DVb/z1d4C4G744F31oiIDCstQyQiIiIiIiIiIrErfzX8/nHAtNa6r6v0FjUeSMHpukqfGgaGFV8iY8sMblta1v9EgVtKpnX+zxf5tydnhewuIkNLMwtERERERERERCR2ZeRA3nLv/t5V0NEY3M9dcHrSzdb3UImCjkbrfLe85d4n26VviQHPHc8q9iZuBspRZBWp7u06IjIslCwQEREREREREZHYtuhJqzgxWEVxX1wWOmHQm45G6zx3Ud3kTCuu9EPArcT8NdEJGxjHNEL3E5EhpWSBiIiIiIiIiIjEtrRpsHiLd/+DQ/DcAmtJoUjUVVr9PzjkbVu8xVvDQCLT3em/H2lB477MCIijAsciI0JzekREREREREREJPbdWApt5+DAOmu/yWmtdT9rqfVk+oyFMD7b27+9AU4ftIoZe2oU9Fj0lBVP+sd3NofdASm91BZw15C42gFJKeFrSID1utkd0FJn7XdeitqQRSRyShaIiIiIiIiIiMjosOBhSL0G9q+Fzkar7eRebzLA7gCbHVwt3hvPvpIzrRkFShQMzDi7d9uWHny8yQk126B2H1w4YiUM3BJtMGk+zLzLKiodWCvC5hM7KURsERlyShaIiIiIiIiIiMjocWMpzLgdDqyHY+WA6T0WKkEAgGEVM170pJYeGoyrrd5tV7N3u7Uefr0Ojr+I3+vhq8sFH1ZZX79/PPj1cLX4XKcldAwRGVJKFoiIiIiIiIiIyOiSNg3u2eHzJPt+uFAT4kn2fJi5OPST7NJ/iane7ZY66LgEJ1/xn+nhy+6wZiC4mgMSOSYc22m9bou3WLMNfI+PSxuqn0BEeqFkgYTV5eqmpfYKXR0miSkG9pnjSLSpJraIiIiIiIiIxIiMHLj9MevLvUZ+VyckJve+Rr4MTPcV//2DX4OjP/Zvm1Vs1ZBwLPSvadBxCercNST2WG2djfDySrj5If8YVwMKKYvIsFCyQPw0O128va2Bun2tXDzSSbfLO3UswWYwcX4yjrvSmLc6m/Qc/YcrIiIiIiIiIjEi0QZZc0Z6FGPbxLn++76JgoxcWFpmJQlCScmCOSXWV10l7F1lzQwBOPp0wHVuis54RaRf9Ji4AHC5/gp7Vpzi2dnHqN50gfNVHX6JAoBul8n5qg6qN13g2dnH2HPvKS7XXwkTUaKppaWFjRs3Mn/+fNLS0sjIyOBP//RPeeKJJ3C5XH0HGMb4mzZtwjAMz5eIiIiIiIiIjBG2MMsDTS2E+6vCJwoCOYrg/mrrvJDXmTCg4YnI4GhmgXB8exMH156hs7E76FiaYxy29ARczd201vkkBkw4sbOZ0/tbWbhlOnNKM4ZxxPGltraWoqIiTp48CUBqaiqdnZ28+eabvPnmmzz//PO8+uqrZGVl9R5oGOL/4Q9/4Nvf/vaAxiEiIiIiIiIio1BGDny+AlIy+3deSqZ13nMLvDMMRGREaWZBnKvZfJFXVtb5JQquK07j7l3X8VDDXB44dQNfPDqHB07dwEMNc7l713VcV+zNInc2dvPKyjpqNl8cieGPeV1dXdxzzz2cPHmSqVOnsm/fPi5fvkxbWxsvvPACdrudw4cPc9999414/O7ubh566CE6OjooLAzzZICIiIiIiIiIjF5m8IOmLC3rf6LALSXTOj/4QgOLJyKDomRBHDu+vYnX1n3g2U/PHUdJZQ737J5Fbkk6KVmJfv1TshLJLUnnnt2zKDkwi/SccZ5jr637gOPbm4Zt7PHimWee4ciRIwCUl5ezePFiABISEigtLWXr1q0A7N69m1dffXVE42/evJnXX3+d++67jyVLlvR7LCIiIiIiIiIS45JS/PdnFVtLCg2GowhmLfVvS0weXEwRGRAlC+LU5forHFx7xrM/pXA8X6i6nukLI1sTbnpRGl+ovp4pheM9bQfXnonZGgbTp0/HMAx++tOfetqOHDniWVe/qcmb6PjOd76DYRjceuutIzFUPz/5yU8AWLRoUcin9VeuXElOTg6A38823PGdTiff/OY3mThxIt///vf7PQ4RERERERERGQXSZ/rv56+JTtzAOIHXEZFhoWRBnHpt/QeepYfSc8bxmYpZJGcm9nGWv+TMRD5T4Z1h0NnYzWvrP+jjrOF37tw56uvrAbjllls87YcPHwYgNzeXjIyMoHbfviOhra2N119/HYC77747ZB/DMCguLgbglVdeGbH4X/nKV7h8+TL/+q//yuTJk/s1DhEREREREREZpSItaNyXGVGKIyKDomRBHGp2ujhR3uzZv7Nser8TBW7JmYncWTbds3+ivJlmp2vQY4ymqqoqAFJSUpg7d66nPVxSwN2+YMGCYRphaO+++y7d3VZC5+abbw7bz33s7NmzNDQ0DHv8H/3oR7z66qssXryYL33pSxFfX0RERERERERGmUvHvdt2B6RkRSfu+GwrXqjriMiwUbIgDr29rcFTJ+a64jSmF6X1fkIfphelcd3SnhhmT/wY4r75n5+fT1JSUlC7b7Lg0qVLnDx5Eug9WfDMM894ljAayFdlZWWf43bPhgBrGaVwfI/5njMc8c+cOcNXv/pVxo8f76lvICIiIiIiIiJjVJPTu21Lj25sm9273XwyurFFJCJJfXeRsaZuX6tne96a7KjEnLcmm1N7rbin91+Gx6ISNiqqq6uB4BkEb731VlC7O4GQlJTE/Pnzw8YcP34811577YDHZLPZ+uzT0tLi2U5NTQ3bz/eY7znDEX/NmjU0NTXx+OOPk5ubG/G1RURERERERGSUczX33adf8SK/pyEiQ0PJgjjT5erm4pFOz/60CAsa92XaQu8N5Qs1HXS5ukm0xcbEFXeywHemwPvvv+8pahwqWTB37lxSUlLCxiwtLaW0tHQohjtqPPfcc7z88st85CMf4e/+7u9GejgiIiIiIiIiMtTSZni3W+qg41J0liJqb7DiuU0IvwKCiAyd2LibK8OmpfYK3S5rDaI0xzhSsgZWqyBQSnYSaQ6r0HG3y6Sl9kpU4g5WY2MjTqc1Rc43WeBOClx77bVMnTo1qH2k6xUA2O3e6XdtbW1h+/ke8z1nKOOfO3eOv/mbvyExMZEf/ehHfss7iYiIiIiIiMgYlTjOf7/uYHTing6IE3gdERkWShbEma4O07NtS4/uyz/O7o3X1Wn20nP4uJcaClxWqK/ixoHtI2HatGme7TNnzoTt53vM95yhjP/1r3+dixcvsnr1am688UZaW1v9vlwub5HrUG0iIiIiIiIiMgqZ3f77NVGqXxgUJzbuK4nEGyUL4kxiiuHZdjV399Kz/660eOMlJhu99Bw+7733HgAzZ84kOTnZ0x5qBsHFixd59913AfjkJz/Za9zt27czZcqUAX/99re/7XPsc+fOJSHB+it69OjRsP3cx6ZMmUJ2duQ1KAYT3z1b44c//CF2uz3o67HHvEUr3G1f+9rXIh6biIiIiIiIiMSgpIAlm0/ugbrKwcWsq4STe/3bEpND9RSRIaZkQZyxzxxHgs26kd9ad4WOS11RidvRcJXWOmvpoQSbgX1mbEwXO3/+PGAVJPYVagbBz372M0zTZOrUqX3OLGhvb+fDDz8c8FckT9mnpqbyiU98AoA9e/aE7GOaJnv3Wv+hLlmypM+YwxlfRERERERERMaY9JmQYPNv27sKOhoHFq+j0TrfV4LNuo5EV5cLLh2H80es711aAUKCKVkQZxJtCUyc783O1h+8HJW49Qe969pPyk+JmeLGWVlWkZ1jx455EgcffvghH3zwAeBNFjidTr797W8DsG7dOs8T9+E8+OCDmKY54K+ioqKIxv/AAw8AcODAAX73u98FHd+xYwfvv/8+AF/60pciihmN+JWVlb3+fN/61rc8fd1tP/jBD/o9PhERERERERGJIYk2mDzfv63JCS8u63/CoKPROq/J6d8+Od+6jgxekxNe2wDPFcBmO5TlwU/zre+b7Vb7axuCXwOJW7FxR1eGleOuNM/221sbohLTN86MxROiEjMalixZQkJCAi6XiyVLlvDaa6/xX//1XwCkp6eTkpLCD3/4Q2677TYuXrzIbbfdxiOPPDLCo/Z64IEHmD9/PqZpsnz5cl599VUAuru72bFjB1/5ylcAuPvuu/nUpz4VdP4zzzyDYRgYhkFlZWXU44uIiIiIiIhInJl5V3DbB4fguQWRL0lUV2n1/+BQiPiLBz42sbTWwy9XwI9nw+83wYdVwTMJulxW++83Wf1eutc6T+Ja0kgPQIbfvNXZVD9+AUw4taeVM5WtTC9K6/vEMM5UtnJqb6u1Y1jxY0VeXh7//M//zDe+8Q3eeust7rjjDs+sgZaWFmbMmOHpW1payrZt2xg3LjaWUAKrMPMvf/lLFi1axMmTJ1m8eDGpqal0d3fT0dEBWLMjnn/++ZiMLyIiIiIiIiJjTP5q6wZzoCYn/HwRzFoK+WtgxkIY73OPqL0BTh+0ihkH1igIjC8D99522L8WOhuDj9kdYEsHVzO01PkcMOHYTqjdD4u3wI2lwzVaiTFKFsSh9Bwbs5enc2JnMwC/XnWGL1RfT3JmYr9jdTZ28etVZzz7s5enk54TW1PFNmzYwMKFC9m8eTP79u3j4sWLnmN5eXksXbqUVatW8ZGPfGTkBtmLWbNmUVNTw/e+9z1efPFFnE4n48aNY968eXzxi1/k4YcfxmYb+J/5UMcXERERERERkTFs/GTodkFnk7V/cq83GWB3gM0OrpaAm9M9kjOsGgXt54dvvGNZ9WY4sM6/bVaxlbxxLISULG97xyWocydvempZdjbCyyuh7RwseHjYhi2xwzBNc6THEBcKCgrMN998M+L+7777LnPnzh2y8Vyuv8J/zjtOZ2M3AFMKx/OZiln9Shh0Nnbxq2UnOXuoHYDkzAS++PYcJkyLnSfzQ5k1axa1tbX8x3/8Bw8++OBID0eGyFD/HRIRERlOhmFUmaZZMNLjkNjQ388WIiIiUfXahuCZBdd8FOwz4MQvgUjuNRow+8+g5TScq/I/dOujcPtj0Rpt/Hhvu3Wj3y0jF5aWWUmCvtRVWoWmfWsXfPoFzTAYw8J9vlDNgjg1Ydo4Fm6Z7tk/e6idny/4I2cqWyM6/0xlKz9f8EdPogBg4ZbpMZ8oaGpq4tSpUwAUFOjztoiIiIiIiIhIv9TuC247VwUXamDZ89bN/msLgosUJ9qs9lsftfpdqAlOFIC1FI70T2u9tfSQ29RCuL8qskQBgKMI7q+2znPbv1Y1DOKQkgVxbE5pBrc/NdWz3+y8wi8WneSl4pO8v6uZjoarfv07Gq7y/q5mXio+yS8WnaTZecVz7PanpjKnNGPYxj5Qhw8fxjRNUlJSuPHGG0d6OCIiIiIiIiIio0eXCy4c8e7f7jPDoMkJFX8O5w7Dbd+AL9fCqmPwwBHr+5drrfZzh61+vk+xf9JnJsGFmuBivNK7A+u9NQoycuDzFZCS2b8YKZnWeRk51n5noxVX4opqFsS5/IcnMv6aJA6uPeNZkujUXm/B4jTHOMbZE7jS0k1r3ZWg85MzE1i4ZfqoSBQAVFdXA5Cfn09Skn79RUREREREREQi1lzrvZFvd8CtX4f0Wf4FdftVsyDTW1D3v//d6tPlsq6TNWcYfqAxoMkJx8q9+0vLQicK3H+uVzsgKQXSZwbP/kjJtM7/+SJr/1i5Fd+dQJAxT3dLhTmlGUy7PZXX1n/AifJmv6XlQiUIAGtpueXp3P7k1JhfesjX4cOHAbjllltGeCQiIiIiIiIiIqPM1Q7vti3d+n5jKcy43XoK/Vg5fjeWQiUIADAgbzksehLSpvXEs3sPd3VGc9RjW802PH/ms4qtJYXcmpzW8dp91owQ3xkbiTaYNB9m3gX5q70JAUcRzFrak/AxrfNVQyJuKFkggFXDoHjHdTQ7Xby9rYHT+y9zoaaDbpf3H/gEm8Gk/BRmLJ7AvNXZpOfYeokYm5599lmeffbZkR6GiIiIiIiIiMjok5Ti3XY1e7fTpsE9O3xuTu8PXk4o0QaT8mHmYv+b0554LT59k4dm/GORbw2J/DXW99Z6+PU6OP4iYQtOd7ngwyrr6/eP+ydv8td4Z4fU7leyII4oWSB+0nNsFD42BR6DLlc3LbVX6Oo0SUw2sM8cR6JNZS5EREREREREROKSe+maLpc1a6DjEqRkeY9n5Fg3lm9/zLvsTVendfM/1LI3bu0N3lkIiTarr/QtsIaEYyG8t91/WShfdoc1I8TVHDDrw4RjO63EwOIt1mwDN3fSJ9xrJ2OKkgUSVqItgcw5yuSKiIiIiIiIiAjepWs+rLL26w7CnJLwfSOtO3D6oHd7Ur5uTEcqsIbEO8/BgXX+fWYVWzMFHAv9Ezsdl6zXr2YrnNxjtXU2wssrYdFTVjzVkIg7ekxcREREREREREREIuP71HnN1ujE9I0zc3F0YsYD3xoSpumfKMjIhS9UwvLdVkLHN1EA1v6cEuv4Fw74Lwt1YB2Y3d591ZCIG0oWiIiIiIiIiIiISGTyVwOGtX1yD9RVDi5eXaV3fXyMnvgSEd8aEq1nvNtTC+H+Kms2QSQcRXB/tXWeJ169d1s1JOKGkgUiIiIiIiIiIiISmYwcqxiu295V0NE4sFgdjdb5bnnLgwsfS3h+dSB6Chln5MDnKyAls3+xUjKt8zx//j3xVEMirihZICIiIhIlLpeL48ePc+TIEY4fP47L5RrpIYmIiIiIRN+iJyE509pucsKLy/qfMOhotM5rclr7yZlWXIlcog2y8vzblpb1P1HglpJpne8r6wbVkIgjShaIiIiIDILT6WTDhg0UFBRgt9vJy8sjPz+fvLw87HY7BQUFbNiwAafTOdJDFRERERGJjrRpsHiLd/+DQ/DcgsiXJKqrtPp/cMjbtniLFVf6Z1yad3tWsbWk0GA4imDWUp/4EwYXT0YVJQtEREREBqC+vp4VK1Ywe/ZsNm3aRFVVVdBMApfLRVVVFZs2bWL27Nnce++91NfXh4koIiIiIjKK3FgKi57y7jc54eeLoLwYju+C9gb//u0NVnt5sdWvyedhmkVPWfGk/660erfz10Qnpm+cK5ejE1NGhaSRHoCIiIjIaLN9+3bWrl1LY2Nj0DGHw0F6ejrNzc3U1dV52k3TZOfOnezfv58tW7ZQWqoPQyIiIiIyyi14GFKvgf1robPRaju511uw2O4Amx1cLdBSF3x+cqY1o0CJgoHpcsGlY979SAsa92WGT5xLf7Cuo6WI4oJmFoiIiIj0w+bNm1m5cqVfoqC4uJhdu3bR0NDAqVOnOHr0KKdOnaKhoYFdu3ZRXFzs6dvY2MjKlSvZvHnzCIxeRERERCTKbiyFB9+GvBWA4X+spQ4uvhMiUWBY/R98W4mCwWiutW7kg5WYScmKTtzx2VY8sOI310YnrsQ8zSwQERERidD27dtZt26dZz83N5eysjIWLgz9BE9WVhYlJSWUlJRQWVnJqlWrPLUL1q1bxzXXXKMZBiIiIiIy+qVNg3t2WEsL1WyD2v1wocZ7IxusJ9Mn5cPMxZC/GjJyRm68Y8XVDu+2LT26sW1273ZXZ3RjS8xSskBEREQkAvX19axdu9azX1hYSEVFBZmZmZ42l8tFbW0tHR0dpKSkMHPmTGw2a7puUVER1dXVLFu2jEOHrEJua9eu5fbbb2faNBVyExEREZExICMHbn/M+nI/kd7VCYnJkD5TS9lEW1KKd9vVHN3YrhbvdmJydGNLzNIyRCIiIiIRWL9+vWfpoZycHE+iwOl0smHDBgoKCrDb7eTl5ZGfn09eXh52u52CggI2bNiA0+kkMzOTiooKcnKsp6gaGxtZv379CP5UIiIiIiJDJNEGWXNg0s3WdyUKos83AdNSBx2XohO3vcG7dFSizbqOxAUlCyS8LhdcOg7nj1jffaeOiYiIxBGn00l5eblnv6ysjLa2NlasWMHs2bPZtGkTVVVVuFz+/1e6XC6qqqrYtGkTs2fP5t5776WtrY2ysjJPn/Lycs/SRCIiIiIiIhFLtMGk+d79uoPh+/bnPt9pnziT8pXoiSNahkj8edaW2wcXjoRYW24+zLxLa8uJiEhc2bZtG6ZpAlYx4w8//JDPfe5zfkWO3RwOB+np6TQ3N1NX5y3kZpomO3fuZP/+/WzZsoWlS5eyd+9eTNNk27ZtPPbYY8P144iIiIiIyFgx8y74sMrartkKc0q8xwZ6n69mq0/8xUM6fIktmlkgltZ6+OUK+PFs+P0m6x+ZwAxjl8tq//0mq99L91rniYiIjHH79u3zbM+YMYOVK1f6JQqKi4vZtWsXDQ0NnDp1iqNHj3Lq1CkaGhrYtWsXxcXFnr6NjY2sXLmSGTNmeNr2798/LD+HiIiIiIiMMfmrvdsn90Bd5eDu89VVwsm9oePLmKdkgcB72+GZeXC8HDD9j9kdMHGe9d2PCcd2Wue9t324Rhq3Wlpa2LhxI/PnzyctLY2MjAz+9E//lCeeeCJoyYuRjr9p0yYMw/B89eX1119n5cqVOBwOkpOTmTx5MnfeeSc/+clPPE/xioiMJJfLxZEjRzz7P/7xjz3bubm5VFZWsnv3bkpKSsjKyvI7Nysri5KSEnbv3s2BAwc8tQoAnn76ac92TU1NVP49FxERERGROPfSF+CZmwZ4n+8m63yJW4Zuxg2PgoIC880334y4/7vvvsvcuXOHcEQ9qjfDgXX+bbOKIX8NOBZCis9Nj45L1tpnNVutTKWvRU/BgoeHfrxxqLa2lqKiIk6ePAlAamoqXV1ddHZ2AnDLLbfw6quvBt2gGon4f/jDH/jIRz5CR0eHp623f2P+4R/+ge9+97ue/czMTNra2jw3zIqLi/nFL35BcnJyv3+uYfs7JCJj3vHjx8nLywPAMAzPv2uFhYWeIseRamxsZNmyZRw6dCgo3rFjx5gzZ050By9jhmEYVaZpFoz0OCQ29PezhYiIiIxhr22wZgeEM5D7fL5ufRRu15KpY024zxeaWRDP3tvunyjIyIUvVMLy3db6ZikBN4dTsqz25bvhCwf81zI7sE4zDIZAV1cX99xzDydPnmTq1Kns27ePy5cv09bWxgsvvIDdbufw4cPcd999Ix6/u7ubhx56iI6ODgoLC/vs/+Mf/9iTKFi5ciV1dXVcunSJlpYWnnvuOex2O3v27OHhh5WEEpGRFSoBmpOT0+9EAVhJ0YqKCs8MA9+EqjtJKyIiIiIiErHafaHbB3Ofzy++lkyNJ0oWxKvWeti/1rs/tRDur7KyjJFwFMH91dZ5bvvXqoZBlD3zzDOepS/Ky8tZvNgqKpOQkEBpaSlbt1oFZ3bv3s2rr746ovE3b97M66+/zn333ceSJUt67dvV1cU//uM/ArBgwQJ+9rOfedbuttls3HfffTz11FOAtUyH7/IfIiLDLSEh+O1SWVlZvxMFbpmZmZSVlQW1R7J0m4iIiIiIiEeXyypcHCga9/ncLtQE1zuQMUvJgnh1YD10NlrbGTnw+QpIyexfjJRM6zx35rGz0Yobg6ZPn45hGPz0pz/1tB05csSzrn5TU5On/Tvf+Q6GYXDrrbeOxFD9/OQnPwFg0aJFIZ/WX7lypefpVN+fbbjjO51OvvnNbzJx4kS+//3v93ndN998k7NnzwLwyCOPhLxB9sADD3DttdfS3d3tGaeIyEi4cuWK335xcTFFRUWDillUVMTSpUt7vY6IiIiIiEivmmuDb+RH6z6fW5fLuo7EBSUL4lGTE46Ve/eXlvX/HxC3lEzrfLdj5Vb8GHLu3Dnq660ZD7fccoun/fDhw4BVnDIjIyOo3bfvSGhra+P1118H4O677w7ZxzAMiouLAXjllVdGLP5XvvIVLl++zL/+678yefLkPq9dW+v9T+amm24Ke+0bbrgBgD17elk7T0RkiJ0+fdpvf82aNVGJGxjnzJkzUYkrIiIiIiJx4mpHcFs07/O5dWnJ1HihZEE8qtmGpxr6rGJrqtFgOIpglvvpSLMnfuyoqqoCICUlxa/gbbikgLt9wYIFwzTC0N599126u7sBuPnmm8P2cx87e/YsDQ0Nwx7/Rz/6Ea+++iqLFy/mS1/6UsTXd+vq6urz2B/+8AdP0WMRkeEW+MT/woURTuXtQ2AczSwQEREREZF+SUrx34/6fb4eicmDiymjhpIF8ci38El+dJ6O9IsTY4VP3Df/8/PzSUpKCmr3TRZcunSJkydPAr0nC5555hnPEkYD+aqsrOxz3O7ZEGAtoxSO7zHfc4Yj/pkzZ/jqV7/K+PHjPfUNIjFr1izP9tGjR0P2uXr1Kn/4wx882+fPn484vohINCUne98YOxwOsrK8hcGeeOIJ7HZ7RP/22+12nnjiCc+52dnZOBwOz77NZhueH0hERERERMaG9Jn++0Nxny/UdWTMSuq7i4wpgYVPIi100pcZPnHchU8SY+OmR3V1NRA8g+Ctt94KancnEJKSkpg/f37YmOPHj+faa68d8JgiuSHU0tLi2U5NTQ3bz/eY7znDEX/NmjU0NTXx+OOPk5ubG/G1P/rRjzJlyhTOnj3L448/zn333eeXyAHYunUrFy5c8Ow3Nzf3mtQQERkq6enpIbcBNm7cSGtra0RxWltb2bhxI4888oinzW63e7Z9l8QTERERERHpt6G4zydxRTML4o1v4RO7A1Kyeu8fqfHZVjyIucIn7mSB70yB999/31PUOFSyYO7cuaSkBEzl8lFaWsrZs2cH/PXxj398KH7UYfXcc8/x8ssv85GPfIS/+7u/69e5iYmJbNy4EbCWQ/r0pz9NVVUVLpeLDz/8kO9///s88sgjjBs3znNOQoL+uRKRkfHHP/7Rs93c3OzZvlx/JeJEgVtrayuX673LDfkmYY8fPz6IUYqIiIiISNy55PMZYqju8wVeR8Y03X2LN76FT2zp4fsNhM37dGSsFD5pbGzE6bQKLvsmC9xJgWuvvZapU6cGtY90vQLwf9q0ra0tbD/fY77nDGX8c+fO8Td/8zckJibyox/9KGhWQCTWrFnDo48+CljFkwsKCkhOTmbKlCn83d/9HZmZmXzjG9/w9Pdd9kNEZDj5Jo/r6uq4dOkSx7c38bObBvaG+Wc3Hef49iYaGhqoq6vztPc2y0tERERERCRIk9O7PZT3+ZpPRje2xCwlC+KNb+ETV3P4fgPh8lmiJkYKn7iXGgpcVqiv4saB7SNh2rRpnu0zZ86E7ed7zPecoYz/9a9/nYsXL7J69WpuvPFGWltb/b58ixGHanN77LHHeOONN3jooYeYP38+DoeDj370o3zjG9/g6NGjnnXCs7KymDx5csQ/m4hINI0fP95v/+WvvcUrK+twNXUPKJ6rqZtXVtbx8tfe8mv3rY0gIiIiIiLSL0N5n0/ihmoWxJv0mVYtgS4XtNRBx6XoTFFqb7DigRU/RgqfvPfeewDMnDnT7yZMqBkEFy9e5N133wXgk5/8ZK9xt2/fzvr16wc8rhdffLHPpYjmzp1LQkIC3d3dHD16lLvvvjtkP3eB4ClTppCdnR3xGAYT3z1b44c//CE//OEPe72OezbC+vXr+cEPfhB0/LbbbuO2224Lee5vfvMbAAoLCzEMo+8fSkRkCPjOsFrAUpp+HJ3kZfPT17CApVSzN+g6IiIiIiIifcrI8W4P1X0+gPRZg48po4JmFsSbRBtM8incW3cwOnFP+8SZlB8zxY3Pnz8PBD8VGmoGwc9+9jNM02Tq1Kl9zixob2/nww8/HPBXqKfsA6WmpvKJT3wCgD179oTsY5ome/daN5mWLFnSZ8zhjD9Yp06dYt++fQA88MADw3ptERFf7llqGUzmPv6Xp31K4fgwZ/TO97z7+F9kYCUfampqBj5IERERERGJP1lzAJ+HK4fiPh9Gz3UkHihZEI9m3uXdrtkanZi+cWYujk7MKHCvc3/s2DFP4uDDDz/kgw8+ALzJAqfTybe//W0A1q1b12cx3QcffBDTNAf8VVRUFNH43TfJDxw4wO9+97ug4zt27OD9998H4Etf+lJEMaMRv7Kystef71vf+panr7st1KyCcK5cucLq1avp6uri5ptv5nOf+1y/fzYRkWhx/zu4km+RjFVXID1nHJ+pmDWgeJ+pmEV6jlXAPZlUVmL9m3nixInBD1ZEREREROJHos1/yfGhuM+XlBIzDwXL0FOyIB7lr8aTdTy5B+oqBxevrhJO7u3ZMXrix4YlS5aQkJCAy+ViyZIlvPbaa/zXf/0XAOnp6aSkpPDDH/6Q2267jYsXL3LbbbfxyCOPjPCovR544AHmz5+PaZosX76cV199FYDu7m527NjBV77yFQDuvvtuPvWpTwWd/8wzz2AYBoZhUFlZGfX4g/H+++/zD//wD1RXV9PRYRXe7urq4uDBg9x5553s3buXtLQ0fvrTnzJu3LioXltEpD8uX77MRKZzM3d42u4sm05yZuKA4iVnJnJn2XTP/s3cwUSm09raOuixioiIiIhIHIv6fT6JN6pZEI8yciBvORzbae3vXQX3V0NKZv9jdTRa57vlLfdfL22E5eXl8c///M984xvf4K233uKOO+7wzBpoaWlhxowZnr6lpaVs27Ytpm5MJyUl8ctf/pJFixZx8uRJFi9eTGpqKt3d3Z4b7LfccgvPP/98TMbvTXNzM9/97nf57ne/i2EYZGZm0tLSwtWrVwGrmPLOnTtjoti0iMS3iRMnspi/xOhJtF9XnMb0orRBxZxelMZ1S9M4tbcVA4PF/CW2SbXRGK6IiIiIiMSLLhdc7fBvi+Z9PrDid7k0uyBOaGZBvFr0JCRnWttNTnhxmfUPQn90NFrnNVnFbknOtOLGmA0bNvD666+zcuVKJk6cSHd3t+dYXl4eDz/8MIcPH+aFF14gPT19BEca2qxZs6ipqeGf/umfuPnmmzEMg3HjxvHRj36U733ve7zxxhue5ZZiMX5v1/2nf/on7rjjDqZOncrly5fJyMigsLCQxx9/nD/84Q8UFhZG/boiIv2VkZFBPnd69uetibyYfG984+RzZ0z+HyQiIiIiIjHs0nHA7NnpWUUkWvf5PLUQzJ7rSDwwTNPsu5cMWkFBgfnmm29G3P/dd99l7ty5Qzgi4L3t8PJK735GDiwtA0dR3+fWVVqZRs8/IMCnX4AbS6M8yOibNWsWtbW1/Md//AcPPvjgSA9Hhsiw/B0Skbiw6Z8fJ+0f78boecbioYa5pGRZSxDZ7fZ+LR+UlpZGS0sLAB0NV3l64nsAmHTT9t29fO0bX43y6GWsMAyjyjTNgpEeh8SG/n62EBERkTHqxK/gF/dY22kzoPW099hg7/OlTYfWM9b2534FuZ+O0qAlFoT7fKGZBfHsxlJY9JR3v8kJP18E5cVwfBe0N/j3b2+w2suLrX6+/4AsempUJAqampo4deoUAAUF+rwtIiJ9y7w6zZMoSHOM8yQKADZu3EhaWmRLEqWlpbFx40bPfkp2EmkOa+k7gwTSXVOiN2gREREREYkvhhHd+3yGbhvHI9UsiHcLHobUa2D/WuhstNpO7vUWMrE7wGYHVwu01AWfn5wJi7eMikQBwOHDhzFNk5SUFG688caRHo6IiIwCuek34Z50a0v3f8P8yCOP8Mgjjww49ji7N97sjJsGHEdEREREROJQmrcWJy11cNP90bnPN/MuOLDO2z5h+lD9BBJjlCwQ60b/jNvhwHo4Vo53rTNC/8MBgGEVM170JKRNG45RRkV1dTUA+fn5JCXp119ERPqWnJzs2XY1d/fSs/+utHjj2XyuIyIiIiIi0qfEcf77dQejc5/v+K7eryNjlu6WiiVtGtyzw5pyVLMNavfDhRqr2rlbog0m5cPMxZC/2lr7bJQ5fPgwALfccssIj0REREaLhGtcgA2A1rordFzq8luKaKA6Gq7SWnfFs594zZVeeouIiIiIiAQwAx5mqtkKc0oGf5+vZmvghYbqJ5AYo2SB+MvIgdsfs766XNBcC12dkJgM6TOtf0hGsWeffZZnn312pIchIiKjSPuEi5hc66lbUH/wMrkl6YOOW3+wzbNt0k1b6oVBxxQRERERkTiSlOK/f3KPVazYXdR4IPf56iq9yxa5JWoWdLxQpQoJL9EGWXNg0s3W91GeKBARERmISVMm0kWXZ//trQ3hO3e54NJxOH/E+u775E4A3zhddDF56qSojFdEREREROJE+kxICLhft3cVdDQG943kPl9Ho3W+rwSbdR2JC5pZICIiItILu90OXPbsn9rTypnKVqYXpVkNnqm9++DCkRBTe+dbBcJ8pvaeqWzl1N5Wv+ukpaUN9Y8iIiIiIiJjSaINJs+HD6u8bU1OeHEZfL4CUjIjj9XRaJ3X5PRvn5yvB4jjiGYWiIiIiPRi6kQHifjXKPj1qjN0nqmDX66AH8+G32+y3qAHziToclntv99k9XvpXjrP1PHrVWf8uiWSxNSJjqH+UUREREREZKyZeVdw2weH4LkF1pJCkairtPp/cChE/MUDH5uMOkoWiIiIiPSioeoKBoZf2zXpL2H89GY4Xk5QsS+7AybOs777MeHYToyf3sw16S/5HTEwaKhSgWMREREREemn/NUQ8HkFsGYI/HwRlBfD8V3QHrCcanuD1V5ebPULnFEAVtz81UMxaolRWoZIREREpBedF7v89ud/4nnu+Nwm/06ziiF/DTgWQkqWt73jEtQdhJqtVrExwGZrZulffJXxaRc58vp93utc8r+OiIiIiIhInzJyIHcZvP+ytT9+MnS7oLPJ2j+511uw2O4Amx1cLdBSFxwrOcOqUdB+3trPXeZZSlXig5IFMcw0TQwjRGZQRHplmmbfnUREInSlo9uzff2f7PFPFGTkwtIyK0kA3gLHVzsgKcUqBDanxPqqq7SKhfU8sXPH5zbR3jqRP/53sXWdNu91REREREREBqT9PFzzUbDPgBO/xG8mdKgEAQAGzP4zaDkN56rC9JF4oGRBjEpMTKSrq4ukJL1EIv3V1dVFYmJi3x1FRCKQPTcZgNT0cyxc/r+8B6YWWkXDOi/BaxsiK3B8f7VVNKxnLdCFy/8X9c4FtDVfQ/ZNycP5Y4mIiIiIyFjQ5PTOKnA7VwWdDbDsebhQA7X7re9Bn1XyrZoEk/Lh9W8GL0X0/stWm2YXxI0xXbPAMIwZhmGUGYZRbxhGp2EYJw3D+IFhGFl9n+0X59OGYbxiGMZpwzDaDcN43zCMHYZhFA7V2FNTU2ltbR2q8CJjWmtrK6mpqSM9DJGQXC4Xx48f58iRIxw/fhyXy9X3STKixqVZycfbP7uJlNQWqzEjB5Y+Da98uX8Fjvd9xTqv5812SmoLt3/WmqkwboKSnCKxbDR/thAREZExrGZb6PYmJ1T8OZw7DLd9A75cC6uOwQNHrO9frrXazx22+oWsWdBLfBmTxuxj64ZhzAZ+C1wD/D/gPeBWYD1QbBjGJ0zTvBhBnMeBrwEXgV8AF4Drgc8Cyw3D+JJpms9Fe/zp6elcuHABu92uJ6RF+qGrq4uGhgYmTZo00kMR8XA6nWzbto19+/Zx5MgRvwSBzWZj/vz53HXXXaxevZqcHD2xEWuutHVjzz7N7Pn7vY1z74f//DhP7G1k4z5o7ew7Tlqyyca7dvJI7X645WF44zsAzJ6/H3v2aa605Q7RTyAigzXaP1uIiIjIGPb+r/z3P/aPcHgzdDZa+/2qWZDp91nFiv8y3P7YUIxcYpAxVtf2NgxjL7AEWGea5maf9n8F/hbYaprm2j5iTAHOAOeBfNM0z/kcWwT8GnCaptnnp/uCggLzzTffjHj8pmly7tw5Ll++THZ2NmlpaSQmJqqGgUgIpmnS1dVFa2srDQ0NTJgwgWuuuUZ/X2TE1dfXs27dOl588cWIamkYhsHy5ct58sknmTZt2jCMUCJxdNtFOn/xdT76qaethuy50PAuAPZvRpYocEtLhpbv9uxk3wgN7wFQ9epDpJQ8zrzVE6M4chlLDMOoMk2zYKTHEa9G+2cLERERGaO6XPDkeDB76p/NKoblu6G1Hg6sh2Pl+NUsCMuAvOWw6ElImwblxd4Eg5EA69utZYtkzAj3+WJMziwwDCMX6838SeD/Bhz+FrAa+AvDMB4xTfNyL6FmYi3V9DvfN/MApmkeMAyjBZgctYH7MAyDa665hpaWFpqbmzl37hxdXV1DcSmRMSExMZHU1FQmTZqE3W5XokBG3Pbt21m7di2NjY1BxyZNmkRKSgodHR1cuHDB026aJjt37mT//v1s2bKF0tLSYRyxhHO1rRtH3iFvQ0+iAPqXKAjq35MoAJiR9wZn21XgWCQWjYXPFiIiIjJGNdd6EwUA+Wus72nT4J4d1tJCNdv6rlmQv9q/LkH+Gm+ywOy2rpM1Z+h/HhlxYzJZANzZ8/0V0zT9PnmbptliGMbrWG/4Pwa82kuc44ALuNUwjEmmaXru6BiGcQdgx5o+PCQMwyA9PZ309PShuoSIiAyBzZs3s27dOr+2jIwMOjo66Ozs9EsQACQnJ5OSkkJTUxMAjY2NrFy5knPnzvHwww8P27gltETbFSZOPR58wEgAvG8z/o0jYWP8NfP9z/N/e8Kkqcc4N+7KYIcqIkNjTHy2EBERkTGos8V/37HQfz8jx1pC6PbHrERBcy10dUJiMqTPDD9bYEZAHJfqqsaLsVrg+Iae78fCHHd/4s/rLYhpmg3A14FrgXcMw9hmGMZjhmH8HHgF2AesicJ4RURkjNi+fbtfosBdd6apqYnOztCPoXd2dnoSBb51atatW8f27duHcLQSifHj60lMCnEj3xzgTIAQ5yUmXSE1tX5g8URkqOmzhYiIiMSmDp+SSXYHpGSF75tos2YHTLrZ+t7bskLjs614bu0XwveVMWWszizI6PneFOa4uz2zr0Cmaf7AMIyTQBnwFZ9DfwSeCZxC7MswjNVY05K57rrr+rqUiIiMcvX19axd679kdagl5BwOB+np6TQ3N1NXV9dr/7Vr13L77berhsEI6jjTCuOH/jrtp/W0jkiM0mcLERERiU1JPh9UbFFemcRm97lOanRjS8waqzML+uJezLzPCh+GYXwN2Ak8A8wGJgAfBd4HnjcM4/+EO9c0zW2maRaYplkwebKWHxURGevWr18fskYBQHFxMbt27aKhoYFTp05x9OhRTp06RUNDA7t27aK4uDjkeY2Njaxfv34IRy196U5IHp7rJA7PdUQk6vTZQkREREaGTz01XM3Rje3yWeKo4Z3oxpaYNVaTBe6nezLCHE8P6BeSYRhFwOPAL03T/DvTNN83TbPNNM1q4HPAGeCRnqJnIiISx5xOJ+Xl5UHtubm5VFZWsnv3bkpKSsjK8p8WmpWVRUlJCbt37+bAgQPk5OQExSgvL8fpdA7Z2KV3jWenYJpDWzTdNA0aP5gypNcQkQHTZwsRERGJTa7L3u2WOui4FJ247Q1WPLerbdGJKzFvrCYL/tDzPdy6oe7y3eHWHXX7TM/3A4EHTNNsA36P9Wd4S38HKCIiY8u2bdswTf+HSgsLC6mqqmLhwoVhzvJXVFREdXU1hYWFfu2mabJt27aojVX6x0wwCfnA8NTC4LZIhDzPxBiri0OKjH76bCEiIiKxaVzA8kB1B6MT93RAnKRhWJdVYsJYTRa434AvMQzD72c0DMMOfAJoB97oI457PYBw83zd7a6BDFJERMaOffv2+e3n5ORQUVFBZmZmv+JkZmZSUVERNMNg//79gx2iDFBq0hmMwIkFGTnw+YqBBfx8hXW+D8OAlITTA4snIkNNny1EREQkNk251X+/Zmt04gbGufbW0P1kzBmTyQLTNE8ArwCzgP8ZcPjbWGuD/tQ0zcsAhmGMMwzjRsMwZgf0fa3n+2rDMKb7HjAM426sDwYdwG+j+xOIiMho4nK5+O///m+/trKysn4nCtwyMzMpKyvza3vrrbdwuXT/aCRMyg/xdmlpGaRk+jX9NfPDfvlJybTOD7zOnyRGb9AiEjX6bCEiIiIxa9JN/vsn90Bd5eBi1lXCyb29X0fGrDGZLOjxV8A54CnDMH5hGMZjhmH8GvhbrCnC3/TpOx14F3g1IMZOYD9wLfCuYRg/MQzjccMwfgm8jFXM7FHTNC8O8c8iIiIxrLa2lqtXr3r2i4uLKSoqGlTMoqIili5d6tm/evUqtbW1g4opA5OZFzDldlYxOIoGF9RRBLOW+jVlzkkZXEwRGUr6bCEiIiKxJ9EGSRP82/augo7GgcXraLTO95U0wbqOxIUxmyzoeQKoAHgGuA14BJgNPAUURvIm3DTNbmAZ1oeAd7AKjz0CfAyoAJaapvnkUIxfRERGj46ODr/9NWvWRCVuYJzOzs6oxJX+SZ92xb8hPzqvb2CcoOuISMzQZwsRERGJWdd/1n+/yQkvLut/wqCj0Tqvydl7fBnTxnQpPdM064C/jKDfSawneUIduwL8oOdLREQkSGCyINKCxn0JjNPe3h6VuNI/ied/59/gCP36mt8LH8P4+xCNM/zjJF74HVx3Wz9HJyLDRZ8tREREJCZ98p/hvZ/5t31wCJ5bYC1/Gsms6LpKa0ZBYKLAHV/ixpidWSAiIjJc3nzzTc+2w+EgKysrKnGzs7NxOBwhryPD6OK73m27A1Ki8/oyPtuK59bwXnTiioiIiIhI/MjIges+Fdze5ISfL4LyYji+C9ob/I+3N1jt5cVWv1CJgus+ZcWXuDGmZxaIiIgMh7q6Os92enp6VGPb7XbP9unTp6MaWyLT1XUVT+lhW3RfX2ze17fris91REREREREInX3T+FHOdDtCj52cq+3YLHdYX0GcbVAS11wX18JNiuuxBXNLBARERmkhATvf6fNzc1Rjd3S0uLZNoyQq1rIEHN1ZvrsRPf1xeV9ff2uIyIiIiIiEqm0aZHd2G+pg4vv9J0oACte2rTBj01GFSULREREBmnixIme7bq6Oi5duhSVuA0NDX6zFnyvI8PHxTXenZY66IjO60t7g9+b9CvGNb10FhERERER6cWNpbDoqejEWvSUFU/ijpIFIiIigxT4xP/Bgwc920888QR2ux3DMPr8stvtPPHEEyHjgP8MBhk+nVen+zfUHQzdsb9O+8fpuDI9TEcRERERERGRoae7DiIiIoNks9n89rdu3erZ3rhxI62trRHFaW1tZePGjSHjAIwbN27gg5QBS5w827+hZmvojv0VECfxmtzoxBURERERkfjz3nY4sM67n5ELy/4Tbn0Uri2ARP/PrSTarPZbH4VlP/MvZHxgnRVP4o4KHIuIiAzStdde67e/Z88eKisrKSoqijhR4ObuX1lZyd69e3u9jgyPhOSAN9Un90BdJTiK/JqNv+9H0LpKb5Ex93UCkk4iIiIiIiIRaa2H/Wu9+1ML4fMVkJIJrITbH4MuFzTXQlcnJCZD+kz/BELO3fDiMvjgkLW/fy3MuF11C+KMZhaIiMQYl8vF8ePHOXLkCMePH8flco30kKQP3d3dQW2rVq2isbFxQPEaGxtZtWpVULtpmgOKJ4NjcDW4ce8q6GgkLS2tX7HS0tKgo9E6P+g6XQMcoYiIiIiIxLUD66Gz0drOyPFJFPhItEHWHJh0s/U9cKZBSqZ1nnuGQWejFVfiipIFIiIxwOl0smHDBgoKCrDb7eTl5ZGfn09eXh52u52CggI2bNiA0+kc6aFKCOfOnfNsu+sXOJ1Oli1bNqB4y5Yt87zWvvUQfK8jw8c0Q0zEbHLCi8vY+M2vR5wwSEtLY+M3v249rdMU/HfZNBMHO1QREREREYk3TU44Vu7dX1oWnCiIVEqmdb7bsfKQn11k7FKyQERkBNXX17NixQpmz57Npk2bqKqqCppJ4HK5qKqqYtOmTcyePZt7772X+vr6ERqxhNLZ2enZ9n36/9ChQwOK53uebzzf68jwSbQZoQ98cIhHJpXR8s5LmKbZ51fLOy/xyKQy77TeSK8jIiIiIiISTs02oOdz46zioOVS+81RBLOW9uyYPfElXihZICIyQrZv3868efMoLy8PWl7G4XAwb948HA6HX7tpmuzcuZN58+axfbuKDcWKhoYGv/0vf/nLUYn70EMP9XodGR4TpgbcxM+e691ucsLPF0F5MRzfBe0Br1F7g9VeXmz1830qJ/tG/+tM09syERERERHpp/d/5d3OXxOdmL5x3n85OjFlVNCnUhGREbB582ZWrlzpt6Z9cXExu3btoqGhgVOnTnH06FFOnTpFQ0MDu3btori42NO3sbGRlStXsnnz5hEYvQS6cuWK3/7p06d54YUXyMzMHFC8zMxMXnjhBU6fPt3rdWR4JNoCliH65P+GT78AyZnetpN74Zefh3+fCNuug2fmWd//faLV7lvMODnTOv+T/9v/OuO0DJGIiIiIiPRDlwsuvuvddyyMTtwZPnEuvmNdR+KCkgUiIsNs+/btrFu3zrOfm5tLZWUlu3fvpqSkhKysLL/+WVlZlJSUsHv3bg4cOEBOTo7n2Lp16zTDIAaMGzfOb3/Pnj1ce+21vP322wOK9/bbb3Pttdeyd+9ev/akpBBr58vQ6wpI0jgWwo2l8ODbkLcCCJh50FJnvaFuqQsIZFj9H3zbOn9GwBv5wOuIiIiIiIj0prkWzC5r2+6AlKze+0dqfLYVD6z4zbXRiSsxT8kCEZFhVF9fz9q1az37hYWFVFVVsXBhZNn/oqIiqqurKSws9LStXbtWNQxG2OTJk4PaVq1aRWpq6oDipaamsmrVqqD2a665ZkDxZJBafWZ4+L4BT5sG9+yAL5+AWx+Fawsg0eZ/bqLNar/1UavfPTus88D/DTjA5TND+3OIiIiIiMjY4mrxbtvSoxvbZve5Tmt0Y0vM0iOKIiLDaP369Z6lh3JycqioqOj3UjWZmZlUVFSwYMECnE4njY2NrF+/nh07dkR/wBKRadOmBbU5nU6WLVs2oHjLli3D6XQGtYe6jgyDbp8n/kO9Ac/Igdsfs766XNZTN12dkJgM6TODEwi+fN+Aa2aBiIiIiIj0R/tF77arObqxfRMR7ReiG1tilmYWiIgME6fTSXl5uWe/rKwsZKLA5XJx/Phxjhw5wvHjx3G5gtcGzMzMpKyszLNfXl4e8uayDI8JEyaEbD906BCGYYQ8Fo5hGBw6dCjksYHOVJBBSkz2bvf1BjzRBllzYNLN1vfeEgXg/wa8r74iIiIiIiK+fB9maqmDjkvRidve4L+sqi0jOnEl5ilZICIyTLZt24ZpmoBVzLioqMhzzOl0smHDBgoKCpgwYQJ5eXnk5+eTl5fHhAkTKCgoYMOGDX4JgaKiIpYuXQqAaZps27ZtWH8e8ZoyZUrYY+7XPFK99Z86dWq/YkmUJIz3bg/lG/AEJYNERERERKQfAh9mqjsYnbinA+K4mqITV2KekgUiIsNk3759nu01a9YAVg2DFStWkJuby6ZNm6iqquLq1at+5129epWqqio2bdpEbm4u9957r6dGgTsOwP79+4fhp5BQkpOTQ7YnJiaGbHc4HNx00004HI6Qx8OdZ7PpyfMRcfZ3/vtD9Qb87BvRiSsiIiIiIvEhZaL/fs3W6MQNjDN+UnTiSsxTskBEZBi4XC6OHDni2V+4cCHbt2/nhhtu8FuaKBI7d+7khhtuYPv27X6FkWtqakIuWSQjp6uri9TU1KCliOrq6njnnXeoq6vzazcMg9TUVLq6uoZzmNKXhIDkzVC9AU8cF524IiIiIiISH5Lt/vsn90Bd5eBi1lXCyb3+bba0wcWUUUPJAhGRYVBbW+u5ke9wOHjuuedYuXIlra2tIfs7HA7mzZsX9snz1tZWVq5cyfPPP+/p43K5qK2tHZofQHrV3d0d9lhbWxumaZKTk8Ps2bODZgfYbDZmz55NTk4OpmnS1tYWNlZ/lzSSKBk/2X9/qN6ABz4VJCIiIiIi0psJIZaq3bsKOhoHFq+j0To/kuvImKRkgYjIMOjo6PBsm6bJunXrgvoUFxeza9cuGhoaOHXqFEePHuXUqVM0NDSwa9cuiouLg85Zt26d343qzs7OofkBpFcpKSlBbZMnTyYjw1sEyul0cuLECVwuF1OmTCE3N5cpU6bgcrk4ceKEXz2KjIwMJk+eHBQz3HJHMsSu/7PgtqF4Ax7qOiIiIiIiIuFc/iC4rckJLy7r/+eVjkbrvCZn8LFQ15ExSckCEZFh4Hsz+fTp037HcnNzqaysZPfu3ZSUlJCVleV3PCsri5KSEnbv3s2BAwfIycnxO37mzBnPtm4mj4xQhYfPnz/P9ddfz2c/+9mgZYjOnj3L+++/z9mzZ/3aDcPgs5/9LNdffz3nz5+P6DoyDMZnB7cNxRvwUNcREREREREJ52pH6PYPDsFzCyKfEV1XafX/4FDo4116MDFeKFkgIjIMZs6cGbI4bWFhIVVVVX61B3pTVFREdXU1hYWFQcdsNhszZ84c9Fil/z74IPRTFlVVVdTU1PD888/z6KOPUlBQEHIZooKCAh599FGef/55ampqqKqq6td1ZBgkhKgnEM034KHii4iIiIiI9CYpYJZ79lzvdpMTfr4Iyovh+C5ob/Dv295gtZcXW/18H2jKvtG/b6IeTIwXSSM9ABGReGCz2cjLy+Po0aOetpycHCoqKsjMzOxXrMzMTCoqKliwYIHf0jU33HBDyISEDD3fZaYSEhL8loZyOp38+Z//OUuXLuUb3/gGhYWFtLS00NnZSXJyMna7nUOHDrF161Y2bdoUFNs3npaZGiFdLghXL8L9BnzWUshfAzMW+s8QaG+A0wetYsaBNQp8maZ1nUT9HRYRERERkQilzwQMoOfzyif/tzULYP9a6Gy02k7u9X4WsTvAZgdXC7TUBcdLzoTFW6zPJb/8fE+j0XMdiQdKFoiIDJOuri6//bKysn4nCtwyMzMpKytj0aJFnrarV68OZngyCL7LTGVlZXHx4sWgPnv37mXvXusNmsPhwG6309LSQl1diDdoPnzjaZmpEdJcC2bA36/xk6HbBZ1N1n6/3oBnQIIN2n2WmjKvWtfJmjM0P4OIiIiIiIx9joWQkgUzbocD6+FYOZ5EAoT+fAKAAXnLYdGTkDYteBaCxA0tQyQiMkxOnjzp2S4uLqaoqGhQ8YqKili6dGnI+DK8fJeZunjxYsgZAr7q6up45513+kwUPPbYY55EgZaZGkGh1gFtPw8Z18Psz2I9yeOjpQ4uvhPijbhh9c+43j9R4KZ1QEVEREREpD+aa/EkA+wOK1EA1g3/e3bAl0/ArY/CtQXBs5gTbVb7rY9a/e7ZYZ0H1mxpu6Ono9lzHYkHmlkgIjIMXC4X7e3tnv01a9b02re2tpaOjg5SUlLC1jtwx3E/rd7e3o7L5dJSRCPAZrMxf/58T62BG264gRdeeIG1a9fS2NjY73iZmZls2bLF77XMz8/XaztSAtcBdTtXBZ0NsOx5uFADtfut710ub59EG0zKh5mLre+vfzN0cWPQOqAiIiIiItI/vg822dKDj2fkwO2PWV9dLuumf1en9dkjfWbvy6Da7N5tPdgUNzSzQERkGLzzzjt++4EFjZ1OJxs2bKCgoAC73U5eXh75+fnk5eVht9spKChgw4YNfjUKQsUJvI4Mn7vuusuzvXXrVkpLS3n77bdZsWIFhmH0cqaXYRisWLGCt99+m9LSUrZu3eo5tnjx4qiPWSLkWQe0x81f9m43OaHiz+HcYbjtG/DlWlh1DB44Yn3/cq3Vfu6w1c83UXDzQz4X0TqgIiIiIiLST4bPrV1Xc+99E23WsqeTbra+91UvzdXie6EBD1FGF80sEBEZBr///e892w6Hg6wsa2pgfX0969at48UXX8QMU0DV5XJRVVVFVVUVjz/+OMuXL+fJJ59k2rRpZGdn43A4PMvZ/P73v+cjH/nIkP88Emz16tU8/vjjmKbJnj17qKyspKioiB07duB0Otm2bRv79+/n7f9+h7QrkxhHMlfopHXcBeb9yU0sXryY1atXk5OTA0BlZaVn1ohhGKxevXokfzzxtfD/WDMFBls0bOZdcPTp4Rq1iIiIiIiMZS110HHJuxTRYLQ39FLfQMYyJQtERIaBy+VdliQ93ZoauH379rDL1EyZMoUJEyZw+fJlzp4962k3TZOdO3eyf/9+tmzZQmlpKXa7d2rglStXhu6HkF7l5OSwfPlydu7cCcCqVauorq4mMzOTiUznz1jPLeZDXDQ66fYpMJVgGEw0k3GQxkSyAWhsbGTVqlWePsuXL/ckEWQEhFoH9MbSwRcNc8drqcOzDqgKHIuIiIiISKTMbv/9uoMwp2TwcU8fDLzQ4GPKqKBkgYjIMMjNzfVsNzc3s3nzZtatW+fXJycnh4SEBOrq6vwSBDabDYfDQXd3t2cZosbGRlauXMm5c+doaWnxiyEj58knn2T//v00NjbidDpZvviLrJ/+b9S91B72vVW3y+R8VQfnqzqofvwC1/3ZeH5w+q89r3VmZiZPPvnkMP4UEiTcOqDuomFNTqjZ1nfNgvzV1pqhvrQOqIiIiIiIDFRgfbWardFJFtRs9d9XfbW4oWSBiMgwuPnmmz3bdXV1fomCCRMm0NbWFlSPwM3lcnHixAnAWo5m/PjxtLW1AQQlHHyvI8Nv2rRpbNmyhZUrV7KApRRX/SN1Ve1B/dIc47ClJ+Bq7qa1zmc2iAmn/l87xfwjjZhUs5ctW7Ywbdq0YfwpJIjvG/BQ64AOpmiY7zqgegMuIiIiIiL9kT4TEsZBd8/nypN7oK4SHEUDj1lX6V1iFaz4qq8WN5QsEBEZBi+//HLI9sTERC5fvhzU7nA4SE9Pp7m52VOPAKxliNra2khMTKSrqyvkdf7H//gf0Ru49FtpaSnndowjoTzPr/264jTmrclm2sIJpGQleto7LnVRf/Ayb29t4NSeVgBSSWcV3+PB5aspLf38sI5fQnDf8O9y9b0OqLtoWCR81wFNtOkNuIiIiIiI9E+iDSbnw4dV3ra9q+D+akjJ7H+8jkbrfF+T/6TvYsgyZiT03UVERAaruro6ZLvvDf/i4mJ27dpFQ0MDp06d4ujRo5w6dYqGhgZ27dpFcXFxyPN8HT58OLoDl347vr3JL1GQnjuOksoc7tk9i9ySdL9EAUBKViK5Jencs3sWJQdmkZ4zznMsoTyP49ubhm3sEkaiDSbN9+7XBa7fOUC+64BOytcbcBERERER6b+Zd/nvNznhxWXWjf/+6Gi0zmsKWPVg5uLBjE5GGSULRESGQWtra9hj2dnZjB8/nj179vC5z32O7OxsDMPwfGVnZ/O5z32OPXv2MH78eLKzswd0HRl6l+uvcHDtGc/+lMLxfKHqeqYvnBDR+dOL0vhC9fVMKRzvaTu49gyX61W4esT5vgEPXL9zoHzj6A24iIiIiIgMRP5qwPBv++AQPLfAWlIoEnWVVv8PDgUcMHriS7xQskBEZBiEW3O+sLAQl8tFe3vwuvahtLe343K5KCws7Nd1ZHi8tv4DOhu7AUjPGcdnKmaRnJnYx1n+kjMT+UyFd4ZBZ2M3r63/IOpjlX7yfQPuXgd0MOoqfdYB1RtwEREREREZoIwcyFse3N7khJ8vgvJiOL7LWgbVV3uD1V5ebPULnFEAVtyMnKEZt8Qk1SwQGYVcLhe1tbV0dHSQkpLCzJkzsdm0fEUsGz9+fFBbTk4OFRUVZGWFWfs8jNbWVioqKliwYEFQUeSUlJQwZ8lQa3a6OFHuLX57Z9n0kImCLlc3LbVX6OowSUwxsM8cR6LNP3efnJnInWXT+cWikwCcKG+m2ekiPUd/z0eM+w34sZ3WfjTXAdUbcBERERERGYxFT0LtfuhstPaNRDB7li8+udf7oJLdATY7uFq89dN8+Z6XnGnFlbiiZIHIKOF0Otm2bRv79u3jyJEjuFwuzzGbzcb8+fO56667WL16NTk5uukUazIzM4PaysrKQrZHGq+srIxFixb5tfc38SDR8/a2BjCt7euK05helOY51ux08fa2Bur2tXLxSCfdLtNzLMFmMHF+Mo670pi3OtuTEJhelMZ1S9M4tbcVTCt+4WNThvVnkgC+b8Dd64B+vqJ/CYPAdUD1BlxERERERAYrbRos3gIvr7T2zS5ISoWr7Xg+qELoBAEABiSNh6tt3qbFW6y4Ele0DJFIjKuvr2fFihXMnj2bTZs2UVVV5ZcoAGumQVVVFZs2bWL27Nnce++91NfXj9CIJZQJE/zXrC8uLqaoqGhQMYuKili6dKlfW2pq6qBiysDV7fPWi5i3xqorcbn+CntWnOLZ2ceo3nSB81UdfokCgG6XyfmqDqo3XeDZ2cfYc+8pT40CdxyA0/svD8NPIb1yvwF3i8Y6oHoDLiIiIiIi0XBjKSx6yrt/tQ0wrVnMmbMhIWCmeoLNas/Isfr5JgoWPWXFk7ijZIFIDNu+fTs33XQT5eXlmKb/DUaHw8G8efNwOBx+7aZpsnPnTm666Sa2b98+nMOVXgTOIFizZk1U4gbG0cyCkdHl6ubikU7P/rSFEzi+vYn/nHfcWprI/68vaY5xZM9LJs0xzv+ACSd2NvOf845zfHsT0xZ6kz8XajrocnUP5Y8hkQh8Az6YdUD1BlxERERERKJpwcPw6ResGcxuTU5oPAHdLpgwBTJyre/dLqvd9zNKcqZ1/oKHh3vkEiO0DJFIjNq8eTPr1q3zaysuLmbNmjUsXLjQ76bwpUuXOHjwIFu3bmXPnj0ANDU1sXLlSs6dO8fDD+sf+ZF2/vx5v/2FCxdGJW5gnMDryPBoqb3imTGQ5hjHsecaeW2df1Hi64rTmLcmm2kLJ5CS5a1l0HGpi/qDl3l7awOn9lizEzobu3llZR23PzWVNMc4Wuus+C21V8ickzx8P5iEtuBhSL0G9q/1rgnan3VAkzOtGQVKFIiIiIiISLTdWAozbocD6+FYOX5Pr10+G+Ykw6qltuhJzXyOc0oWiMSg7du3+yUKcnNzKSsrC3uDOSsri5KSEkpKSqisrGTVqlWewrfr1q3jmmuuobRUN6VGUkOD92ljh8MRtRkA2dnZOBwO6uqsG5IXL16MSlzpn64O75sv0zT9EgXpueO4s2wG0xdOCHUqKVmJ5Jakk1uSzpnKVn696gzNTmsZotfWfcCE6d7/qrs6zZAxZAT09ga8t3VA9QZcRERERESGWto0uGeHNWugZptVe+1CDXT5LGudaINJ+TBzMeSv7lmOSOKdkgUiMaa+vp6HHnrIs19YWEhFRUXEhXCLioqorq5m2bJlHDpkrYv90EMPcfvttzNtmm5OjRS73e7ZTk9PHzWxJTKJKYZn+/KZq57tKYXj+UzFLJIzvTMJulzdtNReoavDJDHFwD5zHIk2a1XA6UVpfKH6en617CRnD7Vb8eq98RKTvdeRGKA34CIiIiIiEssycuD2x6yvLhc010JXJyQmQ/pM6/OKiA8lC0RizOrVq7l82SpkmpOTEzJR0NrayqFDh2hubiY9PZ3CwkLS0tI8xzMzM6moqGDBggU4nU4uX77M6tWr+dWvfjWcP4r48C083NzcHNXYLS0tnu3x48dHNbZExj5zHAk2w1qKqOcB8/SccZ5EQbPTxdvbGqjb18rFI51+RY4TbAYT5yfjuCuNeauzSc+x8ZmKWfx8wR+tGQamt5995rgQV5cRpzfgIiIiIiIS6xJtkDVnpEchMU4FjkViiNPp5OWXX/bsl5WVeRIFv/nNbygsLGTChAnY7XaWLFnCihUrWLJkCXa7nQkTJlBYWMhvfvMbwEoYlJWVeWK9/PLLnqWJZPhNmjTJs11XV8elS5eiErehocGzBBHA5MmToxJX+ifRlkBmnv+N/DvLpnO1rZs9K07x7OxjVG+6wPmqDr9EAUC3y+R8VQfVmy7w7Oxj7Ln3FFfburmzbLpfv6wbbJ4ZCBLD3G/AJ91sfVeiQEREREREREYJ3XUQiSH/5//8H892cXGxZ0mhGTNmsHDhQt544w3a2tpCntvW1sYbb7zBwoULmTFjBtXV1RQVFbF06dKQ8WV4BT7xf/DgQc+276yQSPj2940T6joyfMaleZcauq44jbYPu/jPecc5Ud7st5w9WEWQs+clk+YImClgwomdzfznvOO0fdjFdUu9r3XSBP2XLSIiIiIiIiJDR3ceRGLIL37xC8/2mjVrWL9+PQUFBZw5c6Zfcc6cOUNBQQHr169nzZo1IePL8MrJ8V+nfOvWrZ7tjRs3RpwwSEtLY+PGjSHjAMyaNWvAY5TBudLa7dmeMGMcr6yso7PR23ZdcRp377qOhxrm8sCpG/ji0Tk8cOoGHmqYy927ruO6Yu/vQGdjN6+srGPCDG8y4eplbywRERERERERkWgzTNPsu5cMWkFBgfnmm2+O9DAkhrlcLlJSUnD/nbznnnt46aWXBh3XN45hGHR0dGCzaVmM4eZyuUhOTvZrO3DgAEVFRQOOWVlZyaJFi/zaOjs79fqOgC5XN9vs7wYtMQSQnjuOO8tmMH3hBE/fcAWOz1S28utVZ6xaBQESbAarW+ZqKSKROGUYRpVpmgUjPQ6JDfpsISIiIiKDEe7zhQoci8SI48ePexIFaWlpfSYKHA4H6enpNDc3+61ZH+ill14iLS2N1tZWTNPk+PHjzJs3L6pjl77ZbDamTJnC2bNnPW2rVq2iuro6qIB1JBobG1m1apVf25QpU5QoGCEttVe8iQIDz7JDUwrH85mKWXRe6uLQhrMRFTj+QvX1/GrZSc4eaveL1+0yaam9QuYc/6STiIiIiIiIiIwyXS5oroWrHZCUAukzY6LmnZIFIjHCt/hwa2tryD7FxcWsWbOGhQsXkpWV5Wm/dOkSBw8eZOvWrezZsyfoPN94J0+eVLJghJSUlLBlyxbPvtPpZNmyZVRUVPQrYdDY2MiyZcuCClaXlJREaaTSX10dPjMKejbTc8ax6Onp/PUd3+LZI9+nk9D1RnABVdZX8qZU/iL/b3n8hX/g5U/XWjMMfEJ3dWo2oIiIiIiIiMio1OSEmm1Quw8uHLESBm6JNpg0H2beBfmrISMnfJwhpLUMREaB3NxcKisr2b17NyUlJX6JAoCsrCxKSkrYvXs3Bw4cCFofX2LD1772taC2Q4cOsWDBAiorKyOKUVlZyYIFCzh06FBE8WWYJATfxM+7P5MXP/5+74mCAJ208WzN93nx4++Td39mcAdDyQIRERERERGRUaW1Hn65An48G36/CT6s8k8UgLX/YZV1/Mez4aV7rfOGmZIFIjEi3A3+wsJCqqqqWLhwYURxioqKqK6uprCwMORxFcAdOTk5OXz6058Oanc6nSxatIji4mJ27dpFQ0OD3/GGhgZ27dpFcXExixYtCppRAPDpT39aSaIRZfjtZc218eZ3ztPZ2B1xosCtkzY6G7t58zvnyboxcAqiEfIcEREREREREYlB722HZ+bB8XL8lg4AsDtg4jzrux8Tju20zntv+3CNFNAyRCIxY86cOUFtOTk5/V6iBiAzM5OKigoWLFgQdGM51HVk+Gzbto28vDwuX74MQGJiIl1dXQDs3buXvXv3AlZNCrvdTktLS8iaFL7nTZgwgW3btg3TTyAhdfvvXnrXFbLbv3EkbIi/Zn5Q26X3AuJoYoGIiIiIiIjI6FC9GQ6s82+bVQz5a8CxEFJ8Vg7puAR1B6FmK5zsWWK8sxFeXglt52DBw8MyZM0sEIkRoQrTlpWVDaj4LVgJg7KysoiuI8Nn2rRpPP300579rq4uUlNTMQz/J8br6up45513ghIFhmGQmprqSRQAPP3000ybNm1oBy69C/O/6ZTC8QMKF/Y8TSwQERERERERiX3vbfdPFGTkwhcqYflumFPinygAa39OiXX8Cwf8axYcWDdsMwyULBijXC4Xx48f58iRIxw/fhyXK/RTrhI7AosaFxcXU1RUNKiYRUVFLF26tNfryPArLS3lqaee8uy3tbVhmiY5OTnMnj07KKFjs9mYPXs2OTk5mKZJW5t3WZunnnqK0tLSYRu7hBP8yH96zjg+UzFrQNE+UzGL9JxxEV1HRERERERERGJIaz3sX+vdn1oI91dZswki4SiC+6ut89z2rx2WGgZKFowhTqeTDRs2UFBQgN1uJy8vj/z8fPLy8rDb7RQUFLBhw4aQ653LyAssWLtmzZqoxA2ME6owrgy/hx9+mBdeeIGMjAxPm9Pp5MSJE7hcLqZMmUJubi5TpkzB5XJx4sQJv7+7GRkZvPDCCzz88PBMQ5M+dAc/8n9n2XSSMxMHFC45M5E7y6YHHzA1tUBEREREREQkph1Yby0hBNYMgc9XQEpm/2KkZFrnuWcYdDZacYeYkgVjQH19PStWrGD27Nls2rSJqqqqoJkELpeLqqoqNm3axOzZs7n33nuprx/+itoS3vvvv++371vQ+IknnsBut2MYRp9fdrudJ554ImQcgJMnTw7pzyGRKy0t5Z133mHFihVByxCdPXuW999/n7Nnz/q1G4bBihUreOeddzSjIIYkpvi/ftcVpzG9KG1QMacXpXHdUv8YiclKFoiIiIiIiIjErCYnHCv37i8t63+iwC0l0zrf7Vi5FX8IKVkwym3fvp158+ZRXl6OafovT+FwOJg3bx4Oh39FbdM02blzJ/PmzWP79uGtqC3h7du3z7PtcDjIyvKuXbZx48aIlw9qbW1l48aNnv3s7Gy/3wF3AV2JDdOmTWPHjh2cOHGCRx99lIKCgpDLEBUUFPDoo49y4sQJduzYoRoFMcY+03/JoHlrsqMSNzBO4HVEREREREREJIbUbMOzhPCsYmtJocFwFMEs9xLjZk/8oZM0pNFlSG3evJl16/wrahcXF7NmzRoWLlzod7P50qVLHDx4kK1bt7Jnj1VRu7GxkZUrV3Lu3DktZRIDEhK8ubv09HS/Y/2tMxDY3263e7bHjdPNxliUk5PDY489xmOPPYbL5aK2tpbOzk6Sk5OZOXOmClPHuC6Xf7J22sIJUYk7bWFq0HUS9asgIiIiIiIiEptqvQ8Dkx+dJcbJXwMnex7+rd0Ptz8WnbghKFkwSm3fvt0vUZCbm0tZWVnQkjNuWVlZlJSUUFJSQmVlJatWrfKsf75u3TquueYaLWkywq5everZbm5ujmrslpYWz3ZnZ2dUY0v02Ww25syZM9LDkH44e8hbdDrNMY6ULKtWweX6K379/pr5EcW7XH+FCdPGkZKdRJpjHK11VzzXue4uex9ni4iIiIiIiMiw63LBhSPe/UgLGvdlhk+cCzXWdYboSUItQzQK1dfXs3att6J2YWEhVVVVYRMFgYqKiqiurqaw0FtRe+3ataphMMKuv/56z3ZdXR2XLl2KStyGhgbq6uo8+7oJLRJ9nQ1dnm1buvVf6/HtTfznvOMkkxrutJCSSeU/5x3n+PYmAMbZvf9VdzZ2hTtNREREREREREZSc611Ix/A7oCUrN77R2p8thUPrPjNtdGJG4KSBaPQ+vXraWxsBKylSyoqKsjMzPTr09rayr59+ygvL2ffvn1By9JkZmZSUVFBTo5VUbuxsZH164e+oraE99577/ntHzx4MCpxA+O8++67UYkrIl5X2rs9267mbmo2X+SVlXV0NnazjL+KOGGQTCrL+Cs6G7t5ZWUdNZsvcqXFG/vK5e5ezhYREREREREJo8sFl47D+SPWd/dNbYmeqx3ebVt6+H4DYfNZZaBr6FYNUbJglHE6nZSXeytql5WVeRIFv/nNbygsLGTChAnY7XaWLFnCihUrWLJkCXa7nQkTJlBYWMhvfvMbwEoYlJV5K2qXl5d7liaS4RdYoHrr1q1RiRutOCISXub13ul/rXVXeG3dB579z+V+mROV5zBNs8+vEwc+5HM5X/ac+9q6DzxLEAFkzlHBAhEREREREYlQkxNe2wDPFcBmO5TlwU/zre+b7Vb7axusfjJ4SSnebVd0lxjH5V1inMTk6Mb2oWTBKLNt2zbPTeXi4mLPkkIzZsxg4cKFvPHGG7S1tYU8t62tjTfeeIOFCxcyY8YMqqurKSoqYulSq6K2aZps2za0FbUlPN8CxwB79uyhsrJyUDErKyvZu3evX5thGIOKKSLBOi6GXh5oSuF4vlB1PdMjLHg8vSiNL1Rfz5TC8aGvc0HLEImIiIiIiEgfWuvhlyvgx7Ph95vgw6rgmQRdLqv995usfi/da50nA5c+01tLoKUOOqKzxDjtDVY8sOKnz4xO3BCULBhl9u3zVtRes2YN69evp6CggDNnzgT1nTJlCrNnz2bKlClBx86cOUNBQQHr169nzRpvZe79+/cPzcClT7feemtQ26pVqzxLTvVXY2Mjq1atCmr/2Mc+NqB4IhLepWPB0zfTc8bxmYpZJGcm9itWcmYin6mYRXrOuKBjjcc1TVRERERERER68d52eGYeHC8H/FexwO6AifO86997mHBsp3Xee9uHa6RjT6INJs337tdFZ4lxTvvEmZQ/ZMWNAZKGLLJEncvl4sgRb0XtsrIyXnrpJb8+OTk5JCQkUFdXx9mzZz3tNpsNh8NBd3e3Z6kh0zR56qmn/JYeqqmpweVyYbNpqYvhdssttwS1OZ1Oli1bNqB4y5YtC7ms1J/8yZ8MKJ6IhHehuj2o7c6y6aETBe5iRFc7rCmKvk8e9EjOTOTOsun8YtFJv/bzIa4jIiIiIiIiAkD1Zjiwzr9tVjHkrwHHQv+Cux2XrJvZNVvh5B6rrbMRXl4JbedgwcPDNuwxZeZd1owNsP5s55QMPmaNzxLjMxcPPl4vlCwYRWpra3G5rKdK09LS/BIFEyZMoK2tLWzNAZfLxYkTJwBrGZrx48d7lit66aWXSEtLo7W1FZfLRW1tLXPmzBnin0YC3XHHHSHbDx06NKB44c4Ldx0RGTjzqn/h4euK05helOZtaHJCzTao3QcXjvhP/3Q/eTDzLshfDRlW4fnpRWlctzSNU3u9BerNLhU4FhERERERkRDe2+6fKMjIhaVlVpIglJQs60b2nBKoq4S9q7y1Cw6sg9Rr4MbSoR3zWJS/Gn7/OGBaSZi6SnAUDTxeXSWcdC8xbljxh5CWIRpFOjq8FbVbW703jxITE7l8+XJQgVyHw8G8efNwOPynFpmmSVtbG4mJ3idefeN1dg5dRW0JLy0tre9Oo+g6IvEk/Xr/mQHz1mRbG4NcJ9ITx32dXM36EhERERERkQCt9bB/rXd/aiHcXxU+URDIUQT3V1vnue1fqxoGA5GRA3nLvft7V0FH48BidTRa57vlLfc8YDhUlCwYRQIL4Lp1dXkLXhYXF7Nr1y4aGho4deoUR48e5dSpUzQ0NLBr1y6Ki4tDnudLBXBHzvjx/kVNJ0+eTEZGxoBiZWRkMHny5F7ji0h0ZN6Y4rc/beGE3teJDMt/nchpC1N7vY6IiIiIiIgIB9ZbSwiBdTP58xWQktm/GCmZ1nnum9GdjVZc6b9FT0JyprXd5IQXl/U/YdDRaJ3nnu2RnGnFHWJKFowiV65cCXssNzeXyspKdu/eTUlJCVlZWX7Hs7KyKCkpYffu3Rw4cICcnPBZqN6uI0PH5XJx9epVv7bz589z/fXX89nPfjbiJI5hGHz2s5/l+uuv5/z5837Hrl696lnKSkSip8Xp/XuV5hhHivPfrXUe3W/W+qtnnciUkz8kzeEtdOx7HRERERERERGanHCs3Lu/tKz/iQK3lEzrfLdj5d6b1RK5tGmweIt3/4ND8NwCa0mhSNRVWv0/8FlifPEWK+4QU7JgFDl9+nTI9sLCQqqqqli4MLKpRUVFRVRXV1NYWBjy+JkzZwY8Rhm42trakImaqqoqampqeP7553n00UcpKCgIKkBts9koKCjg0Ucf5fnnn6empoaqqqqgWFeuXKG2tnbIfgaReNXt8s4cuP5PdgcXlAo0YQpkzLa+9+bAOmbn7/Ze50qkMxREREREREQkLtRswzObfVbx4NbHB+v8WUt7dsye+NJvN5bCoqe8+01O+PkiKC+G47ugvcG/f3uD1V5ebPXzTdIsemrY6keowPEol5OTQ0VFBZmZmf06LzMzk4qKChYsWBC2KLIML9+aFIZh+NWgcDqd/Pmf/zlLly7lG9/4BoWFhbS0tNDZ2UlycjJ2u51Dhw6xdetWNm3aFBTbN55qUohEX3qOlcBLTT9Hwce+FbpTRg6QAC11cPmstz3BBnYH0B3yiY0/LfwWx1/Lp635GtJnqWaB/P/s/X94VPd95/2/PgwaCZCE+GFjA7IkHIgTsNIS6pTkJiAHF4XaDTWOcXs5W4d4wfdmjdMl9y5pd1vSXL1xetdt7aRZYBOSNuk3tjF22yQ22DSIuA2uY9gNBNuBYCGLH7YBoV8gaWB0vn98ZnTOmR9iZjSj0cw8H9ela2bOnPM+hzkzw5zzPp/3GwAAAAA82l5y7zeuz07MxvVuU922vdKSLdmJW2oWPmwbRe99yK08cHKP+9pW1UrBKinUY88VxCqvsSMKRrHRNMmCAjJjxoy4aTt27Eg7URBVU1OjHTt2qKmpyTf9+uuvzygeRqaiwq1FPnXqVF24cCFunj179mjPHvuFUltbq6qqKvX09Ki9PcEXioc3Xnl5eRa3GoAkzVk9WS3rzmrJpx5VeUW3/8nxk6Srl5MP3RwMSV0nIg+MNH6CnT+ivKJbSz71qPZ89680Z3VmPUwAAAAAAEUoHJLOH3Efp9rQ+Fpme+KcP2zXE+DitYzcskaavcT2fzgW09MwUYJAkmRsM+Omx0el9JAXZYgKyJkz/g7kzc3NWrZs2YhiLlu2TCtWrPBNi10PRkddXd1QeaELFy4kHCHg1d7ertdff/2aiYItW7YMJQqCwaDq6uqys8EAhgQrx6lq6indfOtL/idMQLp6SXENjqtqpWnzIyMKvBybKDAB39Sbb31JVVNPKVjJf9sAAAAAgIjuNnsiX7LHlxVThp8/VROmuser4ZBdDzJXOVO6a6f04Anptk3SjEXxyZdA0E6/bZOd766do54okBhZUFBiTwqvX+8OLbrrrrv0wx/+MOVYd955p37wgx8MxYlerS4l742A3AoGg7r11luHeg28//3v15NPPql169apu7v7GkvHq66u1vbt2339DRobG+P6HQAYuZ62K5r/kWdkYs/lO2E91iJtfknq9VUAS5zkqyyXNt8hbVwW9k0346T5H3lGPW1NqpnL6CAAAAAAgKSrbklrBauzGztY5d4PU9I6KyY32JJOS7a4SZjwgBQol6rrxsToDS5RLCChUMj32NvQOJ1EQez8sY2RY9eD0XPHHXcM3d+2bZvWrFmjN954Q/fcc09ace655x698cYbWrNmjbZt2zY0ffny5VnbVgCuUE9YdR/Yn/C5zS+ZmERBcr0Ddv5EbvrAT3SlN5zwOQAAAABACRrvlrRWKP0LTYcV6nHvB7hoLesCQWnKXGn6Ans7BhIFEsmCgtLT435Ia2trNWVKdoYWTZ06VbW1bimMTK5iR3asW7dOxtgThbt371ZLS4tmzpypnTt36q233tKmTZu0aNEilZWV+ZYrKyvTokWLtGnTJr311lvauXOnZs6cqZaWlqFRI8YYrVu3btT/TUAp6D/Xp6k3vBX/xI2L1TvgxE8fRu+AI924OG76tBtOqO+9vkw3EQAAAABQbLxXo/e0S/0XsxO3r8Otpx8I2vWgJFCGqIAEAm4N6+rq7A4tqqpyhxZRpiZ/GhoatHr1aj3zzDOSpLVr1+rQoUOqqalRQ0ODtmzZoi1btigUCqmtrU0DAwMqLy/39TuI6uzs1Nq1a4cer169Wg0NDaP67wFKxaRJZzRu3KB/4uQG6e7nJbmJXecvk8cwX/Q8uPt56XsLfU2Rx40b1KTKM5KmZWWbAQAAAAAFLhCUpt8qvWtLWqt9vzR31cjjnvKMnJ/eOGauekfuMbKggESb1ErZv/rfO2rhvffey2pspOfxxx9XTU2NJKm1tVUrV65UZ2enb55gMKi5c+dqwYIFmjt3bsJEwcqVK9Xaak801tTU6PHHHx+NzUcWhEOD6jw+oAtH+tV5fEDh0OC1F0JelZVfip+4YodUUZNZwIoau3zseoKXM4sHAAAAAChOdW5Jax3elny+dHjj1FHSupSQLCggM2bMGLrf3t6uixezM7Soo6PD1zz5hhtuyEpcZGbmzJnaunXr0OMDBw5o4cKFamlpSWn5lpYWLVy4UAcOHBiatnXrVs2cOfod1JG67taQDnzpHT296FfaXvWG/mHecT3Z+Cv9w7zj2l71hp5e9Csd+NI76m6lp8hYNGlKl39CfbNUu0zqPZNZwN4zdvn6FTHr6cwsHgAAAACgODWukxTpfXdyt9TeMrJ47S3SyT2RByYSH6WCZEEBmTp1qu/x/v2Jm2mmKzZOtnohIHNr1qzRE088MfS4tbVVTU1Nam5u1nPPPaeOjg7f/B0dHXruuefU3NyspqamoREFkvTEE09ozZo1o7btSM+lM1e0+5639d2bj+nQo+d17mC/BkP+GveDIUfnDvbr0KPn9d2bj2n3p9/WpTNX8rTFSCRQdZ1/QuN66c2npO/Mzyzgd+bb5RvXx6zn+gy3EAAAAABQlCY3SPNWu4/3rJX6OzOL1d9pl4+at9rGR/aFQ9LF49K5I/Y2PDYuDqVnQQFZsGCB7/G2bdu0atWqEcfdts0/RCl2PciPhx9+WNdff70eeuihoTJEe/bsGWpYXFtbq6qqKvX09PhGhkTV1NRo69atJArGsONPdWn/Q6c10BlfZmjiDeM1fpLR1UuOLr9z1X3CkU48061Te3u1dOsszV0zeRS3GMnF5N4v/lJ6eVPm4QY6pR/dJ/1fW2KeMJnHBAAAAAAUp6bHpba99liyq1V6dqXthZdOadz+TrtctHdeeY2Ni+zpapUOb5faXpLOH/EnCKL9J+rusKM58pSkYWRBAYmtW7979+6US9Mk09LSMnTyOdl6kD9r1qzR0aNHdc8998gY/0nC9vZ2vf7663GJAmOM7rnnHh09epREwRh2+GsX9OJ97b5EQXVDmapvDmpc0OjyO1fVfeKKLr9zVeOCRtU3B1XdUDY070DnoF68r12Hv3YhUXiMtkueckMV00aWKPD61y/ZeInWAwAAAACAJFXOlJa7Ja119oD0vYWplyRqb7Hzn3VLWmv5VhsXI9d7Rvrne6Rv3iy9+qhtSB07kiAcstNffdTO94NPZ17aeARIFhSQc+fOxU1bu3Ztxif3Ozs7tXbt2rjp3kbKyL+ZM2dq586dOnHihDZt2qRFixbFNTQOBoNatGiRNm3apBMnTmjnzp30KBjDjj/VpZc3nB16PH6SkYzU3XpF3SdCCcsQdZ8Iqbv1imSk8RPdxNHLG87q+FMx9fIx+q72ufcHPP1kblycWTzvct544YHM4gEAAAAAitsta6Qmt6S1ulqlp5ukXc3S8eekPn9Ja/V12Om7mu18XW5JazU9YeNh5KIlio/vkuQ/36OqWmnafHvr40jHnnFLFI8iyhAVkCNHjgzdN8bIcRy1trZq5cqVGcVbuXLlUG37aDxJ+vnPf67PfOYzI99gZFVDQ4O2bNmiLVu2KBQKqa2tTQMDAyovL1ddXV1cAgFj06UzV7T/odNDj01AunrJiZuvsrZMwepxCnUPqrfd05/Aka5edmQCkhO2k/Y/dFozl0zUpJllcXEwSsZPcO87kdEikxvssE+5fWDMF1OMd/fz9qqOrlY3niQFyke8qQAAAACAIrXwYWni9dLeh2xJIsk2K442LK6qlYJVUqhH6okvaa3yGjuigERBdhz6mrRvg39afbPtT1i7VKrw9I3tvyi175cOb7ONqiW3RPHl9+y+HQUkCwrItGluKYroiX1JOnDgQKLZr8m7nDfeddddl2h2jCHBYFBz587N92YgAy8/ctZXeih6wl+Sbmqu1Pz1UzVz6SRVTAkMTe+/GNaZ/Zd0dFuH3t7dG7fcQOegXn7krJp33pTz7UcSwZr4aSt2SBU1qqysVG9vb8qhKisrbV3JFTvs1R3XWg8AAAAAAFG3rJFmL5H2PSIdi7maPVGCQJJkbDPjpscpPZQtbz7lTxRMnmOP82uXJp6/Yoo0d5X9a2+xjaajoz32bbBJoFFI4lCGqIDceOONvscPPvhgVuJ+7nOf8z2eMWNGVuIC8OtuDenEru646dVzyrSqpUF3vVCvOauqfYkCSaqYEtCcVdW664V6rdpX7+tdEHViV7e6W0Nx0zFKLvzC/7i+WapdJknavHmzTQCkoLKyUps3b7YPapdJ9Sv8M3T8InYRAAAAAAD8KmdKd+2UHjwh3bZJmrHINtD1CgTt9Ns22fnu2kmiIFt6z9jRHVE3LpbuP5g8URCrdpl0/yF/ieK9D41KDwOSBQXk9ttv9z0+deqUnnzySdXU1CScv7a2Vh/84AdVWxtb98qqqanRk08+qVOnTg27HgDZcXR7R1x5uhsWT9C9B9+nWUsnpRRj1rJK3Xvofbph8QT/E04kPvIjtjFR4/qhuxs3blRPT48cx7nmX09PjzZu3JgwjiRp8IoAAAAAAEjJ5AZpyRbp/p9JD/dIa49Jf3DE3j7cY6cv2WLnQ/bse8QtAxUtUVxRk16Mihq7XHTfDHTauDlGsqCA/PKXv/Q93r17t2bMmKGjR4/qnnvukTHG93x7e7tef/11tbf7hxgZY3TPPffo6NGjmjFjhvbs2TPsegBkR/tL/lI01Q1luvP5epXXBJIskVh5TUB3Ph8/wuDU3ksj3kZkqDomKZvq1QLXMjsmTuXs7MQFAAAAAJSWQFCaMleavsDexo40QHZ0tUbKP0VEShRnJFqiOOrYLn8j6hwgWVBAurvjy5esXbtWEydO1M6dO3XixAlt2rRJixYtimt2GwwGtWjRIm3atEknTpzQzp07NXHiRK1duzYuZjq1tQGkJhwa1PnD/b5pt++YlXaiIKq8JqDbd8zyTTv38z6FQ4NJlkBOeXsJVNX6mxSNxISpNl6i9QAAAAAAgLHl8HYNlZXwlCjOmK9EsROJnzskCwpIdXV13LTW1latXLlSnZ2damho0JYtW/Szn/1MPT09OnbsmI4cOaJjx46pp6dHP/vZz7RlyxY1NDSos7NTK1euVGtrfDYq1draAFLX03ZFjqeCzE3NlZq1bGSftVnLKnXTCjeGc8WuB3lw6ifu/WD8d/WIBKs863k5u7EBAAAAAED2tL3k3o8tLZwpb5y2vdmJmQTJggLy4Q9/OOH0AwcOaOHChWppaRmaFgwGNXfuXC1YsEBz5871jTRoaWnRwoULdeDAgbTWAyBz4X5/s4L566dmJW5snPCAk2RO5NTVy+79UPwosBEJ9bj3w33ZjQ0AAAAAALIjHJLOH3Ef56JE8fnD8X0Ts4hkQQG5cOFC0udaW1vV1NSk5uZmPffcc+ro8Dc67ejo0HPPPafm5mY1NTUlHFGQynoAZCjm23amp6HxY489pqqqKhljrvlXVVWlxx57zBNnoj+wv3UJRkv1Te79nnap/2J24vZ12HhRVfQsAAAAAABgTOpuc0/k56pEcThk15Mj43MWGVnX3+/WO580aZIuXYpvZrpnz56hhsW1tbWqqqpST09PXJPjWN54AwMDWdxqAJZ7xX9lbZkqpri9CjZv3pxyr5De3l5t3rxZGzdulCRVTB2vytoy9bZHyw8xsiAvrl/kf9y+X5q7auRxT+0ffj0AAAAAAGBsuOrpVZnLEsXh3J27ZWRBAamoqBi6P3XqVH3oQx8adv729na9/vrr10wUfOhDH9LUqW4pk/Ly8pFtKIA4V3rdxsPBav9Xb7pNxWPnL6ty4125RIPjvBgX06j68LbsxI2NEyDHDwAAAADAmDTePXeb0xLFgdydu+WsQwGpq6tTMBhUKBRSe3u7fv7zn+v3f//3tXv37oxjNjc36x/+4R80bdo0SbbXQV1dXbY2GUDEhcNudjnUnfyE/td1JOlz/1m3Jpx+pceNd+Hn/brhtkkJ50MO9ceUbzu5W2pvkWqXZR6zvUU6ucc/re985vEAAAAAAEDuVNdJgaAtFRQtUZyNUkTeEsWBoF1PjjCyoIAEg0Hdeqt7snD//v164YUXtHv3bt+og1RUVFRo9+7deuGFF7R/v1vmorGx0dcMGUB2eK/4722/ov6L4azE7e+46ilBJF25zMiCvJgwLX7anrVSf2dm8fo77fJx65meWTwAAAAAAJBbgaA03XOhZ/v+5POmw1uieHqjXU+OkCwoMHfcccfQ/W3bbHmKFStWqK+vT08++aRmzpypceMS79Zx48Zp5syZevLJJ9XX16cVK1b44kjS8uXLc7j1QOkaP9H/uTyzP77nSCbO7L/sX88Evtbzwls7MKqrVXp2ZfoJg/5Ou1xXgkb0wcpMtg4AAAAAAIyGOvfcbU5KFNfl9twtZ5UKzLp162SMkSTt3r1bLS0tQ8+tWbNGp0+fVjgc1oULF/Ttb39bf/3Xf61vf/vbunDhgsLhsE6fPq01a9YMLdPS0jLUENkYo3Xr1o3qvwcoFdN/fYLv8dFtHVmJGxsndj0YJZNuTDz97AHpewttSaFUtLfY+c8eSG89AAAAAAAg/xrXSbLnbodKFI9Ee4unRLGJxM+dok4WGGNmG2N2GGPOGGMGjDEnjTF/Y4xJu1iUMWaJMWaXMeZsJNZZY8yLxpiVudj2ZBoaGrR69eqhx2vXrlVnZ2fcfFOnTtUDDzygL3zhC3rggQd8DYyjOjs7tXatW+Zi9erVamhoyMl2A6UuUGZ8j9/e3avTLek1No51uqVXb+/xx4hdD0bJpbPJn+tqlZ5uknY1S8efs7UGvfo67PRdzXa+RCMKUlkPACCnivHYAgAAAFk2uUGa5567zWqJ4nmrbfwcKtpkgTHmZkkHJX1W0quS/lrSW5IekXTAGJOgwHTSWP9d0k8kfVzSbkmPSfqBpCmSlmV1w1Pw+OOPq6amRpLU2tqqlStXJkwYDKezs1MrV65Ua6s9KVVTU6PHH388y1sKIKq7dSBu2o/XntZAZ2a9CwY6w/rx2tPx6zkZvx6MgtgEQCIn90j/fLf0jWnS9puk78y3t9+YZqfHNjNOuJ6LI99WAEDaivnYAgAAAFl225c0NLogayWKTSRubhVtskDSNyRdL2mD4zirHMfZ5DjO7bI/7N8v6c9TCWKM+bSkr0jaK2mO4zifdRznjxzHWec4zm9I+uMcbX9SM2fO1NatW4ceHzhwQAsXLvSVJBpOS0uLFi5cqAMH3DIXW7du1cyZM7O9qQAi+s7FJwW6W6/ohytPZhTvhytPqrv1Stz0/vey0zgZabrwhueBZ3TH9R+Wbv6Uf5ok9bRLF163tz7Gzn/9hxPHu/B6drYXAJCuoj22AAAAQJa9ukWS4z7OSoliJxI3t8bnfA15YIyZI+m3JJ2U9LcxT/+ppHWSPmOM2eg4TtIuo8aYcZK+KumypN93HKcndh7HceLP1o2CNWvW6L333tOGDRsk2REGTU1NWrFihdavX6+lS5f6Sg91dHRo//792rZt21CPgqgnnnjC18cAQPZV1AQSTu8+2uZ7/J91a0rx7HLXx00vn5J4Pcix8d5eEZEfBJMbpE/vlSpq7JUAh7dLbXul84elcMidPRCUpjfaJkWN6+xy/Z32h0FXq3w/MIKTcv9vAQD4lMKxBQAAALKkq1U6tivx9KebpPoVUuN6afZSaYKnbHxfh3Rqv21mnKzywLFdNk4OSxEVZbJA0u2R2xcdxxn0PuE4To8x5t9kf/D/pqR/GSbORyU1SHpG0kVjzG9LWiCpX9KrjuMk6UA5Oh5++GFdf/31euihh4bKEO3Zs2coGVBbW6uqqir19PSovT326lVbemjr1q0kCoBRYMr9V5Z/4MEpuvKz72vp6j/Thj+XetOoHlRZLv3eF1dp/64/Udmi39Mb33JL05ggPQvyYkJ8Xxit2GETBZL9j3zJFvsXDkndbVJ4QAqUS9V1NmHgVVFjl3+6yT+9vCYHGw8AuIaSOLYAAABAFhzerqGL/uqbpfkPSHsfkgY67bSTe9xkQFWtFKySQj0JKg/IngNYvlU6+u3IMo6NvyR3IwyKtQzR+yO3x5I8fzxyO+8acX4jcvuupEOSfijpUUl/I+mnxpj9xpjrki1sjFlnjHnNGPPauXPnUtrwdK1Zs0ZHjx7VPffcI2P8Jwnb29v1+uuvxyUKjDG65557dPToURIFwCjpe89/oeCSB57Ris/8P6qY2KPNd9gEQCoqy6XNd0gVE3u04jP/j5Y8sHPY9WCUzFzsf1zfLNUuSzxvIChNmStNX2BvYxMFUbXL7BUHw60HADAaSubYAgAAACPU9pJ7v3G9dMsa6dP/IlXOip83aYli2fk//S92+cb1nvh7s7/NHsWaLJgcue1K8nx0es014kRrfDwkaYKk5ZKqZK8A2iPblGxn4kUlx3G2O46zyHGcRdddl/R3/4jNnDlTO3fu1IkTJ7Rp0yYtWrRIwaD/5FMwGNSiRYu0adMmnThxQjt37qRHATCK3vpHt9LAgttfUtkrXxh6vPFTc9RzvEWO41zzr+f4Pm38lDvcrOzf/1ALbnf/I3rrn+IqGmA0BCvl6y3g/Y98JHxxTGQ9AIBRVlLHFgAAAMhQOCSdP+I+rl0qvfmUtPMTUu/p9GL1nrbLvfmULVkUFVvaOMuKtQzRtUTP6DjDziVFi38bSfc4jvPzyOOjxpjflb26aKkxZvFYGDbc0NCgLVu2aMuWLQqFQmpra9PAwIDKy8tVV1cXl0AAMHounbZX/E+sfk+LP7HZfeLGxdLdz7vlaq6ldpl0/yHp2ZVDjW4Wf2Kz3nrtQ7rcfb0un2FkQV6EQ/L9l1K7NOmsafH+IJBj15NsJAIAIF+K8tgCAAAAaepuc0/kV9VKr39P2rfBP099s70wcOZiKdTtligOVktnDkR6Fuy28w50Sj+6T2p6wsbraXdLG0+Zm5N/QrGOLIhe3TM5yfPVMfMlEy0E/pbnx7wkyXGcPtkrgCTptrS3MMeCwaDmzp2rBQsWaO7cuSQKikw4NKjO4wO6cKRfnccHFA4NXnsh5FWw2p4fWPKpRxUs77YTJzeklyiIqqixy0Ua2gTLu7XkU49KksqqaHCcF92eRtVVtVLFlOzEnTDVxku0HgDAaCn5YwsAAACk4Gq/e99x/ImCyXOke1uk1S9Ic1dJk2b4SxRPmmGnr35Bunefv4nxvg2St3VWOI3Gl2kq1pEFv4zcJqsbGk29JKs7GhunM8nz0R/8E1LbLCBz3a0hHd3eofaXenXhyIAGQ+7Fa+OCRtNuLVftHZWav26qqhtIDo01db9TqUtHj+vmWz215bwNcNMV0wD35lv3qmrqKdXd9esj3lZkIOQp/xSsTj5fJoJVnvX0Zjc2ACAVHFsAAADg2sZXuPe9ZYeyUFVCvWfc5wMpNr7MQLGOLNgXuf0tY4zv32iMqZL0MUl9kl65RpyfSLoqaa4xJtHZ1wWR25OZbyowvEtnrmj3PW/ruzcf06FHz+vcwX5fokCSBkOOzh3s16FHz+u7Nx/T7k+/rUuUoxlT5q+dpvkfeUZmXGTfDdcAN1WeBrhmnKP5H3lG89dOG1lMZKbvgns/1J3d2N5ERN/57MYGAKSCYwsAAABcW3Wdp3Rw5PxPlqpKDMULBO16cqQokwWO45yQ9KKkekmfj3n6y5ImSfp7x3EuSZIxpswYc4sx5uaYOOclPSU75PhPvM8ZY+6QtEJ2uPHuHPwzAB1/qkvfn39cJ3Z1x1XBrawt09T55aqsLfM/4UgnnunW9+cf1/GnrjUaHqMlWDlOtfM85Ydz0AB39rxXFKwsyq/1sa/Ck6TpaZf6LyafNx19HTZe1ITp2YkLAEgZxxYAAABISSAoTYkZjJqNqhJeU96f016GxVqGSJL+k6SfSnrCGPMJSW9I+oikJtkhwn/smXdW5Pk22YMAr/8SWe6PjTEfl/SqpDpJvyspLOk/Oo7TmbN/BUrW4a9d0Msbzvqm3dRcqfnrp2rm0kmqmOLWpu+/GNaZ/Zd0dFuH3t5ty5QMdA7qxfva1ffeVTU+zNXm+db5y15Nu9FTnSAHDXCn3/hLu55bs1wGB9dWXuV/3L7f1hocqVP7/Y+DlSOPCQDIBMcWAAAAuLYyz3F7NqtKnIy0tyqbNLJ411C0l6BGrgBaJOk7sj/IN0q6WdITkhY7jnMh+dK+OO9Flv9rSbWSNki6XdKPJC1xHGdn1jceJe/4U12+REH1nDKtamnQXS/Ua86qal+iQJIqpgQ0Z1W17nqhXqv21au6wR1t8PKGs4wwGAP6jp9QYPxV+yBHDXAD46+q71cnshMX6Zl0o//x4W3ZiRsbJ3Y9AIBRwbEFAAAAUnLF02swB1UldOVSdmImUcwjC+Q4Trukz6Yw30lJZpjnO2SvAvovWds4IIlLZ65o/0NuE5QbFk/Qnc/Xq7wmMMxSrlnLKnXvoffphytP6p0DfZKk/Q+d1swlEzVpZtk1lkbOOP3u/Rw2wDXOQHZjIzWX/KOAdHK31N4ysisI2lvcKwe86wnOTTQ3ACDHOLYAAADAsMIh6WJuq0ro4i/tenJUiqhoRxYAherlR85qoHNQklTdUJZWoiCqvCagO593RxgMdA7q5UfOXmMp5NKkWZ5O9TlsgDtxZu7q1mEYV/vjp+1ZK/V3Zhavv9MuHytMMggAAAAAgDGpu82eyJdyVlVC4ZBdT46QLADGkO7WkG1mHHH7jllpJwqiymsCun3HrKHHJ3Z1q7s1NOJtRGaq6zyjOnLYANe3Hoye8RWeB5GLSbtapWdXpp8w6O+0y3W1+uNJUqA80RIAAAAAACDfro5OVYlcXkhIsgAYQ45u75Ace/+m5krNWjayZqazllXqphWRGE4kPvIiEFv0rX1/wvnSFtMAN1CWtOoBcqm6zjME0HGnnz0gfW+hLSkUFQ5JF49L547Y27AnidfeYuc/e8ATPBIvELTrAQAAAAAAY4/3QsIcVpXI5YWERd2zACg0J3/ofvDnr5+alZjz10/V23tsc5W2H/Vo8ZYbshIXafJdeS7buHbuqpHHjW2Ay5Xn+REIStNvld49aB8veFD6xTft/a5W6ekmaXKDpHF2JMigJ0EwLhgZTjjoGU0QseBz0i++Ze9Pb8xZTUIAAAAAADBC1XWSCUhO2K0qkY1SRN6qEiaQ0wsJGVkAjBHh0KAuvuEOI5q5dFJW4s5cOnHofsfrAwqHBrMSF2mqrpNjPCWCog1wR6K9xdcA1zFlXHmeT3V3uPd7T0m//aR/2GFXq9R1wp8okOzjrhP+REGw2i7fe8oTf3luthsAAAAAAIxcIOi/iDMXVSUC5Tm9kJBkATBG9LRdkRO29ytry1QxJbNeBbEqpo5XZa09Se2E7XqQB4GgzPWN/mlZboBrrv8QV57nU+M6DfUXOLlbunBUvn4DXlW10rT5boOiOMYuP5QMMpH4AAAAAABgTAqH/H0LYqtBZMob52q/v5xxllGGCBgjQj3hofvB6uHzeOHQoHrarijc7yhQYVRVV6ZAMPkyZVXuc1d6w0nnQ47V3eGWqZHcBrh3Py9V1KQeJ64BbjQ+V57n1eQGad5q6dgz9vErX/E/X98sNa6Xapf6hyH2X7RXGxzeZpMMkhTq8i8/b3WkjBEAAAAAABiTutskeSp6RKtK1C7LPGZ7i6+qhDRo1zNlbuYxh0GyABgj+i+4J/FD3fGlgrpbQzq6vUPtL/XqwpEBDYbcJqrjgkbTbi1X7R2Vmr9uqqob/FeXX+lx4/WdJ1mQN43rpFe/qoQNcFfsSO0/j/YWO6IgNlHAledjQ9Pj0lvPS1cvu9Mmz4ns36WJl6mYYvtXzF2VeP+On2jjAgAAAACAscs7qiBqz1rp/kPpXSQalaCqhCQpPBA/LUsoQwSMERXT3Nxdb/sV9V+0J/Uvnbmi3fe8re/efEyHHj2vcwf7fYkCSRoMOTp3sF+HHj2v7958TLs//bYunbHlhvo7rqq33S09VDGdHGHeRK88jxVtgLurWTr+nG1c49XXYafvarbzxSUKxJXnY4qn9NCNi6X7DyZPFMSqXWZ/RNy4OHE8AAAAAAAwNpkEp9qjVSXSLUOdrKqEXVEGG5cazhoCY0Swyv+Fcmb/JYUHHO1/6LSe7/y2ntc3NKDLSZZ2lTsTtfKZ/6RTez+rpVtnKRD0f4EEK8kR5lXT49JbL0hXL9nHJqChZhUn97hDy6pqpWCVFOpxO957eZcbP4krz8eKfY+4+3ZyQ/olpiQ7/93P2xEnXa023r5HpLt2ZntrAQAAAABAtoST9AnNWlWJa6wnCzhrWKTCoUF1Hh/QhSP96jw+oHAovqwNxpbyaf6Gxq/80Tt68b52DXQOppwokKQBXbbzdw7qxfva9cofvTPsepAHg54vdSdsy8zEZoV72qULrydIFBg7v+MpJzVI0+oxoatVOrbLfbxiR2bDDCW73Iod7uNju5L/SAAAAAAAAPnXe8q9X1UrNT3hPh5JVYmmJ2y8qEunc7P9YmRBURlJTXvk37uv+JMBF99wO5unmihINP/FN/0d0t995bLqV1ZnsIXIipfWSYMxXeuj9e0nN9gha93t/nnGBaXqWskZjFxpHvN+GAzZuL/7w9xuO4Z3eLuG+lHUN4+sgZFkl69fERlt4tj4S7aMLCYAAAAAAMi9YLW08GFp4vXS3oekgU47PZ2qEuU10vKt0i1rpMNbR2WzSRYUgUtnrujlDWd14tluX99Ur2hN+3MH+3Xoq+d18+pqLXn8Rk2aWTa6G4ukut8KJZxuApI8F5F/XUeSxvjPutW3nJOgl3FPa+L1YBR0tUpv/ch9POE6e6J/oMt9PmrSDXYEwdXL0qV3pM4T/ljlk20Soe+cffzWj+zy9C3In7aX3PuN67MTs3G9+yOibS/JAgAAAAAAxirvOZlQt729ZY00e4ktL3xsl3wnbxMlCCRJxvambHpcqpwZidfjPl1dn8WN9qMMUYE7/lSXvj//uE7sik8UVNaWaer8clXWxiQEHOnEM936/vzjOv5U1+htLIaXpDdJohP+qUi6HL1S8+dnf+F/fNfT0gOvS/PuUdyOufSO1PWWvfUxdv4HXrfLDxcfoyccks57EnmpNjS+ltmeOOcP2/UAAAAAAICxZ8pcDZ3f6WmX+i/a+5UzbR/CB09It22SZiySAjFVXwJBO/22TXa+u3a6iYK+Dk9iwUTWkxuMLChgh792QS9vOOubdlNzpeavn6qZSyepYopbm77/Ylhn9l/S0W0dent3ryQN1bTve++qGh+eNqrbjniVs0fn4zhpFh/7vDn+j+59b5mau3baUQGHt9urx8/93N+HYFyZdN2HpLrlUuM6N1NdOdNTpiYSf/n/HIV/COJ0t7kn8qtqpYop2Yk7YaqN19Nu43e35fRHAQAAAAAAyFAgKE2Y7laBaN8vzV3lPj+5wVYMWLJFCvVKZw7YEQPBKmnmYilYmTjuqf3u/QnT4xMNWcRZwwJ1/KkuX6Kgek6Zbt8xW7OWTko4f8WUgOasqtacVdU63dKrH689re5WezLy5Q1nNeH68Zq7ZvKobDsSm3hD4pJQNyyeIB1IP94NiyfonQN98eu5kdJTeREOSZffdR97ytQ89thj2rz5T9XbeynJwlckvSbpNVVWfk2bN39ZGzdudONEkwWX37XryeF/Gkjiar97P5jlniDBKvd+eCC7sQEAAAAAQPZMvM5NFhze5k8WDF0o+pKtTuCtHhAIStNvleru8F8oGo3jjZ9DlCEqQJfOXNH+h9yu1zcsnqB7D74vaaIg1qxllbr30PvsSeiI/Q+d1qUzV4ZZCrnWfyG+blB1Q5nufL4+o3h3Pl+v6ob4xED/+QzrGmFkLh6Xr1ZYtExN7xlt/u+bhkkU+PX2XtLm/7FJ6j1jJ3jL1MiJrAejbnyFez9alzBbvHUJA+XZjQ0AAAAAALLn0nvu/ZO7pfYWew7nn++Rvnmz9Oqj0rsH48sMh0N2+quP2vl+8Gm7XHuLe5GoJF1+T7lEsqAAvfzIWQ10DkpyTyaX1wSusZRfeU3AdzJ5oHNQLz9y9hpLIZeuXBqMm3b7jllp79uo8pqAbt8xK2761cvx68Eo8DYvjpapefMp6dsfVG//1bRC9fZdlb79Qbt8tExNVPfJ7Gwv0lNd547o8NYlHClvXcJA0K4HAAAAAACMPeGQ1H/BP+0H90rf+aB0PKa58bAc6dgzdrkf3Ot/qu9CTvsZUoaowHS3hmwz44hkJ5PDoUH1tF1RuN9RoMKoqq5MgaA/NxQ9mfyPTSclSSd2dau7NaTqBkqY5MPARf8V/zc1V2rWsiS1ylI0a1mlblpRqbf39Lrr6WBkQd4Fq6VDX5P2bYh7yvnL5IuZL3oehLqkH91nM8reMjXIj+hwwXcP2sexdQkz5a1LOL2RElMAAAAAAIxVvqoSxt6PliTKxECX50EkXrSqxPT5mccdBsmCAnN0e8fQey72ZHJ3a0hHt3eo/aVeXTgyoMGQm60aFzSadmu5au+o1Px1U4cSAr6TyY6Nv3jLDaP6b4JVPsWf9Jm/fmrC+f6zbk0r7vz1U33JgvKpmY1UwAh5a81deidhoiAj+zZIFZ4G5dX12YmL9NXd4SYLYusSZspbl7Bu+cjjAQAAAACA3PBWlSifIg10DD9/Va29oDTU7VYVSKa8RhqIVDHoPkmyAFb7S+5J3+jJ5EtnrujlDWd14tnupKNZBkOOzh3s17mD/Tr01fO6eXW1ljx+oybNLPOdTD6195K0Jef/DCQwGPbvvJmeHhSVlZXq7e2NXSSpyko3iTRz6UTfc+GrqQ55QlZ5y8d4h6TduFgZdbC+cbF09kB8PMrU5E/jOunVr0py3LqEtcsyj9fe4qlLaGx8AAAAAAAw9g0kKU9c3yw1rre9LCumuNP7L9oqBYe32XMKcfE6c7KZsehZUEDCoUFdODIw9Hjm0kk6/lSXvj//uC1NlEbZqxPPdOv784/r+FNdvpPJ5w/3Kxyipn0+dPyif+h+ZW2ZKjwjDTZv3uxLAAynsrJSmzdvHnpcMXW8KmvdRscXPevBKLqUoCfI5Abp7uczi3f38/7RCsOtB6NjcoM0b7X7eM9aqb8zs1j9nXb5qHmrE+9vAAAAAAAwNviO22NO1E6eI93bIq1+wVYi8CYKJPt47ir7/L37EpwD8MTLYVUJkgUFpKftylBpocraMh37XqdevK99qNlxugY6B/Xife069g9dQyeTB0OOetquZG2bkbr+c24vgWC1/6O5ceNG9fT0yHGca/719PRo48aNvuXLqtx4/RfoWZAXVxMkaVbskCpqMotXUWOXjxUeiJ+G0dP0uB0aKNnhh8+uTD9h0N9pl4sOXyyvsXEBAAAAAMDYNWVu4uk3LpbuP2hHE6Sidpl0/6FINYo01pMFJAsKSLjfzSA5jqOXNwx/BXFlbZmmzi/3XVWeyMsbzsoZdGOHByhTkw8Tb3SrgoW6szu640qPG2/iDKqP5cX4Cv/j+uaRlaiR7PL1K/zTAuUji4mRqZwpLd/qPj57QPreQltSKBXtLXb+s57SVMu32rgAAAAAAGDsCgSl8ZP806JVJdK9WLSiJnFVifGT7HpyhLOGBSRQYYbuXzp9NeE8NzVXav76qZq5dJKvjE3/xbDO7L+ko9s69Pbu+Nr3l8648QLlJu555N6spkq99uXzkqTe9ivqvxj27cNM9XdcVW+7O1pkZlNq5YyQZbG9BBrXZydu43pPXfsE68Hou2WNdPk9t4l1V6v0dJNN7DSul2YvlSZ4Gpj3dUinonUJ9/hjNT1h4wEAAAAAgLEvUC5dveQ+zkZViaeb/PFziGRBAamqK9O4oLGliGIu/q+eU6bbd8zWrEhT3HBoUJ3HBxTudxSoMKqqK9OcVdWas6pap1t69eO1p9Xd6ik3FIk3Lmjnxei7esk/muDM/kuas6p6xHHP7L887HqQJ0mGnpkvphlndopD2DC6Fj4sTbxe2vuQ24To5B43GVBVKwWrpFCP1NMev3x5jR1RQKIAAAAAAIDCEA75GxFns6pE9HzCQKddT45GF5AsKCCB4DjVzCtTxy9Cvuk3LJ6gO5+v18DFsA586R21v9SrC0cGhvobSDYJMO3WctXeUan566bq3kPv0w9XntQ7B/p8saa8P6hAkOpU+RDu82eAjm7ryEqy4Oi2Dv96KDOVHxded+9X1foa2VRWVqq3N37ETzK+ZtcTptp40RPOF16Xrv+1EW4ssuKWNdLsJdK+R6Rju+TL8iZKEEiSjG1m3PQ4pYcAAAAAACgk3W2SPBfp5qSqxKBdT476FnBWuMCUVfrL0lQ3lKnpW7O078HT+u7Nx3To0fM6d7DflyiQbOPicwf7dejR8/ruzce07z+eVtO3Zqm6wT+KYPwk3hL5Epjgf/z27l6dbkn9BHIip1t69fYefwxK2ufJ2Vfd+0F/Emjz5s3+BMAwKisrtXnzZv/EYFXi9SD/KmdKd+2UHjwh3bZJmrEoPvsfCNrpt22y8921k0QBAAAAAACFZqDH/zjVhsbXEltVIjSy84XDYWRBgenvCPsez7u/Rs9+9C0NdMaXlqmsLVOwepxC3YO+mvVypBPPdOvU3l7d+vA0vfaVc0NPDVwMx8XB6Jg4M3740I/Xnta9h96n8pr0excMdIb147WnU1oPRkHYMyIo1O17auPGjdq4cWPmsUOe/4wGrySfD/kzuUFassX+hUP2KoDwgM3eVdfltDkRAAAAAAAYBf0X3PsxVSVGJLaqRN/57MRNYEwnC4wx10u6RZIcx/lJnjcn78KhQXX9yj3hOOUDQd+Jfim9BscDnYN67SvnNOWWoC6+aeN2Hg8pHBqkFFEeBALxjaW7W6/ohytP6s7n69NKGAx0hvXDlSf9fSmi6xlPA+u8qK517/e0S/0Xs/OfRl+Hv6RN1eyRx0RuBYI5Gy4IABgexxcAAADImQnT3PvBkZcW9/FWlZgwPbuxPcb6GeFPSmqR9OM8b8eY0NN2xVf26uIbbuKgek6ZVrU06K4X6jVnVbUvUSBJFVMCmrOqWne9UK9V++p95YeiiQJJ0mBkPRh1gYrEJ/HfOdCnpxf+KuWSRKdbevX0wl/F9aMYWk85yYK8mBhTVqZ9f/J5wyHp4nHp3BF7Gw4ln/dUTJzY9QAAAC+OLwAAAJAb3trfMVUlRsxbVSKH1QnG9MgCD85uSgr1xJcaktwGx6leeT5rWWXSBseSFOpNvB7kVlVdmX2nJ+g/3N16Rf/YdFI3rYiOHJmoiqnux7e/46rO7L9sR47sGSapYCLrwejre9f/+PA2ae4q93FXq3R4u9T2knT+iD9BEAhK02+V6u6QGtfZkjbeOF7972V90wEAKEIcXwAAACB3cllVIocKJVkASf0XrsZNq24oS5goCIcG1dN2ReF+R4EKo6q6Ml9pofKagO58vl5PL/xVXKma/vPx60HuBYLjNH6C0dXLCbIFEW/vcRsWV9aWqaxqnK70xPSkGMb4CYYSU/kS20vg5G6pvUWaMk/68Qbp+LNKmCmSbOLg3YP279WvSvNWS02PSxePSSf3xMzLyCAAAAAAAIBR58RcgN2+33+haKZiq0okO3+UBSQLCkjFtPiRA7fvmDWUKOhuDeno9g61v9SrC0cGNBhy3zjjgkbTbi1X7R2Vmr9uqqobgiqvCej2HbP0j00nfTEnTE+/mS5GLhwaVHgg/sN+3YcrVDm7TK3/3OP7LkiaIDBSw+9UqffUFZ072O9fx4BDT4q8SfCa/+BeaTAkDXTFP1dVa+vbhbpjsseOdOwZOwJhXKJhZ1woCQAAAAAAMOrGV/gfx1aVyFRsVQlvuaMsy0mywBiTrRqgN2QpTlEIVvlP4t/UXKlZyyp16cwVfaH5y/rukb/WgC4nXjgk6aD9K390oj7T+If6mxf+VLOWVeqmFZW+0jVllSQL8qGn7YqcsH9adUOZPrW3QeU1gaFk0Km9l3T+cH9cMmh6Y4VmL580lAwa6AzHjRxxwnY9NXNz96WCZBKU9+rzNyhXfbPUuF6qXeofptZ/0WajD2+zIxKkxAkGSTK5yy4DAJAvHF8AAABgzKuu8z+OVpWoXZZ5zPaW+KoSsevJolyNLFimXI6HKFGxtebnr5+q4091af9Dp/XdzmESBTEGdFnfPfzX+sj839fSrbM0f/1UX7KAmvb5Ee6P/8h4R45UNwS1eMsN0hZPmakBR4Hy+DJTkpKOHEk0egGjYNwwn6vJc6QVO2ySIJGKKTYTPXeV/U9iz1rb4yDd9QAAULiWieMLAAAAjHkxDUn3rJXuPyRV1KQfqr/TLh8XP3dyXYvEZOEPEeGQ//jo4i8H9OJ97RroHEw5URA1oMsa6BzUi/e16+IvY0rVhDgOy4dAhf/tHh05knDe4DjVzC3XtAUVqplbnrSsUHTkiG/Zcj5WeeFtSux142Lp/oPJEwWxapfZ/2RuXJz4+er6TLYOAIBCwfEFAAAAxqbuNrmJgsjPzq5W6dmV9sR/Ovo77XJDF4tGf8Y6kfXkRq6SBWcjtz9wHGdcpn+SPpuj7StIZ37iXv1fPi2gVza9m3C+r+tI0r9EXvnSeyr39EPwrgejp6quzHf4On/91KzE9cUxjBzJmylz46dNbpDufj797HJFjV0uUQIi0XoAACh8HF8AAABgbLvquSC7cpZ7/+wB6XsLbbWIVLS32PnPHvDEm+neDw9kvo3XkKtkwauypz1/I0fxS1LXW27t+dBFt7j9DYsnZBTPu5w3Xk9rksa5yD3PoI6ZSydlJeTMpRMTxscYsGJHZsPQJLvcih3Z3BoAAMYyji8AAAAwtnkbHF/t8z/X1So93STtapaOPyf1dfif7+uw03c12/liy097ExGF1uBY0s8kfUrSDGPMbMdxTuVoPSXFeFI7TqRXanVDme58vl6aknCRYd35fP1QA1zH03vVyXVxKiTU0+YmaSpry1QxJTuNpiumjldlbZl6268MrYcGx3kQO0SsvnlkDW4ku3z9Cn+jm+42RhcAAIoRxxcAAAAY26rrpEBQCoek/gvudBOQnMiF2if3uOdxqmqlYJUU6pF62uPjeZeLxgsEc9rgOJcjC6K4+idLKmfFl4/xNsBNV7QBbtx6ZlKmJh9CPe7ojmB1dj+aZVVuvCu94WHmRM5c9fcGUeP67MSNjZPDoWgAAOQRxxcAAAAY2wJBafqt/mmTG6Q/OCLNu0dx7bN62qULrydIFBg7/x8ciS9BPb3RridHcjmyIHoZbZKunin5P5K+POKtKRKVtf6T+MM1wE1VtAHu23vcPgVVN5EsyIf+C+5J/FD34DBzymYou9vsCejxFW7mMokrPW68vvMkC/LCxCSAUm1ofC2zY+PQtxEAUJQ4vgAAAMDYd8NvSO8edB+v2CFN+4B0105bWujwdqltr3T+sD2/FxUI2kRA3XKpcZ2bJFixw5YlGoq/KKebn5NkgeM4XRrZj/honJ9L+vnIt6g4BMr9Jxuz2QDXmywYF6QOUT5UTHM/jr3tV9R/MewvRTT0hfKSdP5Igi+UW6W6O/xfKJL6O64OlSCSpIrpucoRImVVtVJFBrXDEpkw1cZLNFwNAIAiwfEFAAAACk5sCerJDdKSLfYveiFweMD2IEh2IXCiEtQ5lPFZQ2OMcRyHdqmjKHzFf7V5ThrgJlgPRkewyp+kObP/kuasqpZ6z0g/3iAdf1ZJOxSHQzZr+e5B6dWvSvNWS02PS5UzdWb/Zf96KkkG5YW3MUiwOruxg1XeFWU3NgAAo4TjCwAAABS8d37m3h+uBHUgmHrPycb1brLgndcy37YUjOQS49eMMZ93HOeVrG0NhtVzMrUGuP9ZtyacnkxsA9zetiu6/tcy3kxkqKquzHYRiZxTPrqtQ3NueUHa+5A00JlggVp70jnUHXNVuSMde8YOaVq+VUe3fcR9alxkPRh93jJEoe7sxg71eFeU3dgAAIweji8AAABQuMIhWw0kKhclqKPli3LUt2Aklxj/uqR/NcZ8yxhzXbY2CMn1tLllZ2Ib4FZWpte7IHZ+bwPcbs96MHoCwXGa+kH3gz65Z5v0o/v8iYL6Zul3npM+3yGte1t64Bf29vMddnp9szvvQKf0o/s0uXfb0KRp88sVoMxU/vW0S/0XsxOrr4MSRACAYsHxBQAAAApXd5tbNjwXJaglt3xRjoz0rKGR9ICkXxpjPm+M4ZLWHBq4mLwB7ubNm1NOGFRWVmrz5s2+ad4GuKEOGuDmS/2dtjzN+z60Wx//3UfdJybPke5tkVa/IM1dJZVNki4el84dsbdlk+z01S9I9+7z9Sz4+O8+qvd9aLckqe63veVqMKrCA/7H7fuzE/dUTJwwyT4AQEHj+AIAAACF6Wq/ez+XJahjzzFl0UiSBWfk1ruokfSEpIPGmMUj3SgkVuapNR9tgBu1ceNG9fT0yHEcOY6jqwNhXTzWr/OH+3TxWL+uDoSHnuvp6dHGjRuHlo1tgFtWxZXn+TJ/3VRNrH5PS1f/mTvxxsXS/Qel6pukl78kfW+R9LUqacc86e8b7e3Xquz0l79kG6Lcf8guF7F09Z9pYvV7mr8uO02xkYFL7/gfH96WeL50xca5dDY7cQEAGH0cXwAAAKBwja9w7+eyBHWgPLuxPUbSs+AWSV+W9LCkaPH8X5MdOvz3kv6b4zjvjWzz4FU+2d+jYKgBbkR3a0hHt3eo/aVeXTgyoMGQ2x9uXNBo2q3lqr2jUvPXTVV1Q9ATJ6YBbnXiXgjIveqGoD75+cdUMTHyBTC5QVrxLenFB9NvcLziW9Jzvy11tapiYo8++fnHVN1w+6j9WxDjaswV/yd3S+0ttqt9ptpb3AY3UeErieYEAKAQcHwBAACAwlVdZ3sJhENuCepslCLylqAOBO16ciTjS8gdx+l1HGejpIWS/k32KiAncvsfZIcOP2yM4TL1LJnWWOF7fHRbhyTp0pkr2n3P2/ruzcd06NHzOnew35cokKTBkKNzB/t16NHz+u7Nx7T702/r0pkrvjhD6/mQfz0YRV2tmjHtBffxB+6Xvv9R6fguxSUKqmqlafPdmmVDIg2Ov/9Ru3zEjGkvSF2tOdt0XINJkOjZs1bq78wsXn+nXT5OkoQSAABjHMcXAAAAKGiBoDT9VvdxLkpQT2/MWXNjaeQ9C+Q4zi8cx/m4pM9KOud5arKkv5F0yBjzsZGuB1LFVP9AkLd39+rf/+RdfX/+cZ3Y1R13jrCytkxT55ersrbM/4QjnXimW9+ff1z//ifv6u09vf71TBnJgBOMyOHtMtEdOfUD0itfGVmD41e+Ik29RZJs3MPbR+2fgljer9tIhYWuVunZleknDPo77XJDyR9vOWdKOwMAChvHFwAAAChYdXe493NRgrpueXZiJpG1q3Icx/k7Se+XtFX2tHX01HWjpJ8YY/7OGDMjW+srRVV1ZXHTXvvKOQ10us2Jb2qu1Cefu0mf6/iA/uDt9+v3fjFXf/D2+/W5jg/ok8/dpJua3SbIA52Deu0r5+JiJloPRknbS+79jjfc+7ENjmOHMFVMSdrgWB1veuLvzcFGIzXepuSezN7ZA9L3FtqSQqlob7Hznz2QOF6iEQwAABQgji8AAABQcBrXaehCzmgJ6pFob/GUoDaR+LmT1SG8juN0OY7znyR9RNJB+YcO3y87dPgRhg5nX/WcMq1qadBdL9RrzqpqVUzx9x2omBLQnFXVuuuFeq3aV6/qBhICY044JJ0/Ej892uC4dmlqcWqXxTU4HnL+sF0P8m/Bg+79rlbp6SZpV7N0/Dlbi86rr8NO39Vs5/OWk1rwOf+85AoAAEWE4wsAAAAUlMkNtpdoVDZLUM9b7b9AOAdy8qPacZyDsj/o/29JFz1PVUv6K0n/2xizJBfrLmY9bYkbl96weILuPfg+zVo6KaU4s5ZV6t5D79MNiyektR7kWHdb/In8yQ3S3c9LFTXpxaqoscvFfoGEQ3Y9GH2xnep7T0m//aRUXuNOO7lH+ue7pW9Mk7bfJH1nvr39xjQ73dvMuLzGLt97KmY9uatbBwBAvnB8AQAAgILR9Lh7vidbJajLa2zcHMvZFTiOtU126PB3opMjt7dKajHGfNcYc0OutqHYhHoG46ZVN5TpzufrVV4TSLBEcuU1Ad35fOIRBqHe+PVgFFztj5+2Ykf6iYKoihq7fKzwQGbxMDITY77qTu6WJs2QHjgqzbtHcb0GetqlC6+73e6HGDv/A0ft8t4EgiRNujHbWw4AwJjA8QUAAAAKQuVMaflW93E2SlAv32rj5ljOh+s6jnPBcZy1kpZIOiL/0OHflx06/IfGmPTOdpeg/gtX46bdvmNW2omCqPKagG7fMSt+Pefj14NRML7C/7i+2ZYUGonaZVL9Cv+02CvcMTrKq+Kn7VkrjZ8o3bVTevCEdNsmacai+NEBgaCdftsmO99dO+1y3qFoUcHK+GkAABQRji8AAAAw5t2yRmp6wn08khLUTU/YeKNg/KisRZLjOD81xiyUtEHSZtkhw0ZSlaS/lPRZY8zDjuPsH61tKjTBan9u56bmSs1aNrITg7OWVeqmFZV6e0+vu57JlHzNi+o6uce6khrXDz312GOPafPmzert7U24qFdlZaU2b96sjRs3unG8jVCq67K62UhRdZ1sftYzcic6FC1aMmrJFvsXLRcVHrDJneo6fwIhdijakHHsXwBAyeD4AgAAAGPawoeliddLex+SBjrttJN73PN0VbVSsEoK9SSoLCFbemj51lFLFEijMLLAy3GcQcdx/kb2KqBW2bOi0auAFkj6sTHmH4wx1NFIoP9C2Pd4/vqpWYkbG6f/fDjJnMg9T3daT0PjVBMFktTb26vNmze7E2Z7GyPT/TZvAkFp+gfjpycaihYISlPmStMX2FtvoqC9JX4oWtT0+fQsAACUFI4vAAAAMKbdsmZkJahHMVEgjcLIgsjw3w9J+k3P380xs0XPYBpJ90m60xjz3yV93XEczm5GXI3pJTAzxYbG1zJz6UT/ei7RsyAvvI2Hq2qliin2fu+ZlBMFUb29vVLvGVvLbMJUGy/6xdPdZk9AY/TNuVM6/4v46dGhaPUr7EiQ2Uvtfovq65BO7ZcOb4vvUeCL/9vZ32YAAMYYji8AAABQUCpn2pLSXa3S4e1S217p/GFbWSIqEJSmN0p1y6XGdbYCRR5kPVlgjJkp/w/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      "text/plain": [
       "<Figure size 1872x2808 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(26, 39))\n",
    "\n",
    "marker_size = 500\n",
    "mean_field_marker_size = 100\n",
    "\n",
    "x_label_size = 40\n",
    "tick_size = 20\n",
    "legend_size = 25\n",
    "title_size = 35\n",
    "\n",
    "n_rows = 3\n",
    "n_cols = 2\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 1000000, 'Erdős–Rényi'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "beta = 0\n",
    "phi = 0\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.005, 0.01, 0.015, 0.02, 0.025]\n",
    "results = prepare_table_with_result_scenario_1(N, \n",
    "                                                m, x,\n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 1)\n",
    "sub.set_title('A', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "psi = 0\n",
    "color_ = 'k'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.04\n",
    "color_ = 'darkviolet'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.049\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "sub.set_xlabel(r'$\\alpha$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_1$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "sub.legend(fontsize=legend_size)\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 1000000, 'Erdős–Rényi'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "alpha = 0.025\n",
    "psi = 0.049\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.003, 0.006, 0.009, 0.012, 0.015, 0.018]\n",
    "results = prepare_table_with_result_scenario_2(N, \n",
    "                                                m, x, \n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 2)\n",
    "sub.set_title('B', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "phi = 0\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_2_public_op(N, \n",
    "                              results, \n",
    "                              table_mean_field_approx, \n",
    "                              sub, x, alpha, psi, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "\n",
    "sub.set_xlabel(r'$\\beta$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_{1}$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "#sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "constant-implementation",
   "metadata": {},
   "source": [
    "# ... on BA networks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "knowing-stephen",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1872x2808 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(26, 39))\n",
    "\n",
    "marker_size = 500\n",
    "mean_field_marker_size = 100\n",
    "\n",
    "x_label_size = 40\n",
    "tick_size = 20\n",
    "legend_size = 25\n",
    "title_size = 35\n",
    "\n",
    "n_rows = 3\n",
    "n_cols = 2\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 1000000, 'BA'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "beta = 0\n",
    "phi = 0\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.005, 0.01, 0.015, 0.02, 0.025]\n",
    "results = prepare_table_with_result_scenario_1(N, \n",
    "                                                m, x,\n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 1)\n",
    "sub.set_title('A', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "psi = 0\n",
    "color_ = 'k'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.04\n",
    "color_ = 'darkviolet'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.049\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "sub.set_xlabel(r'$\\alpha$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_1$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "sub.legend(fontsize=legend_size)\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "#\"\"\"\n",
    "\n",
    "N, T, topology_id = 2000, 1000000, 'complete'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "alpha = 0.025\n",
    "psi = 0.049\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.003, 0.006, 0.009, 0.012, 0.015, 0.018]\n",
    "results = prepare_table_with_result_scenario_2(N, \n",
    "                                                m, x, \n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 2)\n",
    "sub.set_title('B', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "phi = 0\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_2_public_op(N, \n",
    "                              results, \n",
    "                              table_mean_field_approx, \n",
    "                              sub, x, alpha, psi, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "\n",
    "sub.set_xlabel(r'$\\beta$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_{1}$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "#sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "#\"\"\"\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "motivated-headquarters",
   "metadata": {},
   "source": [
    "# ... on WS3 networks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "closed-configuration",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0Cb0fciPxtgzR3wKTgDTgL3sR59+x/kd+mWmac03TXGma5r3AvwK3A9/r9UhjRG1tLfPnz2fChAmsWbOGqqqqoJkEHo+Hqqoq1qxZw4QJE3jooYeora2N0ohFREREeu8zk37lSxSMK7GWjOgNRxGMmw1Ysws+M+lXvYsnsWJwfr7wTxT4/fx358ZCQH+/n/+g+NI1/0RBX7wf/vGla/6Jgr54P/zjS9d+vTxwf8oj8PNPdytRANB49Tr8/NPW+TeKLz3S498P6RN6P6QnhkR7AH3BNM097ds9eSqs7bzxwH3AKeDfOhz+J2AR8BeGYawwTfNyz0YaG8rLy1myZAkulyvomMPhIC0tjYaGBmpqarztpmmyZcsWdu/ezYYNG1iwYEE/jjj+uN1u1q5dS0VFBU6nk8TERCZNmkRpaSlLly7FZrNFe4giIiIDUkKi302G/MUh+5jf7/x84xshGvMXw6mdwfFlwIqLzxd98PMvvaD3I7bo/Yi+Cwd921lT4HdPB3UJ+/1odlnnZ02GumPB8SUiuv37IX1K74eEa7DOLIiEe9te3zBNs9X/gGmabuBtIAX4VH8PLJLWr19PaWlpQKKgpKSErVu3UldXx+nTpzl8+DCnT5+mrq6OrVu3UlJS4u3rcrkoLS1l/fr1URh9fKiuriY/P5+nnnqKw4cPY5omzc3N7N+/n2984xt86lOf4tKlS9EepoiIyIBzbPdvAhvCLVjZlbGBcYKuI/Eqtj5fHH8tcL+Pfv6DriOhHXw+cL+v3o+O15HQ/md74H5fvR8dryOheRoBvz+bdRFavqnOf3ZHa9t1RETim5IFnbu97fV4J8dPtL1O6oex9Iny8nKWLVvm3R8/fjyVlZVs376duXPnkpkZWGMtMzOTuXPnsn37dvbs2RNQs2DZsmWUl5f329jjRUtLCw888ACnTp1i9OjR7Nq1i8uXL3PlyhVeeeUV7HY777zzDl/+8pejPVQREZEB5+LPn/EtQWR3QHKE6ssOy7LiYS1FdPHnz0Qmrgx0sfX5Yrffk9J99PMfdB3p3K//xrfdl++H/3Wkc/r9iC0f9FPSvb+uIyISw5Qs6Fx622t9J8fb2zM6C2AYxiLDMPYbhrH/woULkRxbr9XW1rJkyRLvfmFhIVVVVcyYEd4TE0VFRRw4cIDCwkJv25IlS1TDIMKef/55Dh06BEBFRQUzZ84EICEhgQULFrBx40YAtm/fzptvvhm1cYqIiAxEyWaDb8eWFtngNrvvOuhJRQF6+fki4p8trl/xbffhzz/Xr0Y29mDV0uzb7sv3w/860rkmv0LQffl+NKmORFguHOqf63x0pH+uM1g19vB+UE/PE5E+oWRBz7U/h2Z21sE0zU2maRaYpllw880399OwwrN8+XLv0kO5ubls27aNjIyMbsXIyMhg27Zt3hkGLpeL5ctjsyjQmDFjMAyDn/3sZ962Q4cOYRgGhmFQX+/7zPb0009jGAZ33nlnNIYa4Kc//SkAxcXFAYmZdqWlpd7//v7fm4iIiHStyfC7AeRp6LxjT3jcvuuQGtnYMljd8PNFxD9bDEnxbffhzz9DhkU29mBlJPq2+/L98L+OhKcv3w8Jz/n/Dt0+Ovgzclg6O+/cH3sWT+BYOfxkSs/O/ckU63wRiQlKFnSu/e5xeifH0zr0GzCcTicVFRXe/bKysm4nCtplZGRQVlbm3W8vwBtLzp8/753xcMcdd3jb33nnHcBafik9PT2o3b9vNFy5coW3334bgPvvvz9kH8MwvDUk3njjjX4bm4iIyGAw4kvfwmy/LeuugaYI1QC6WmfFA0zTuo4Isfb5YuZG33Yf/fwHXUc6l/eXvu2+fD+m/mXnfcXnZr/Pgn35ftwc3c+cA0ZLU3Bbei48uK1n8R7cZp0fznWkawfWw+ulPU+seRqs8w+oFqZILFCyoHPvtb12tmboxLbXztYcjVmbNm3CbPtkXFJSQlFRUa/iFRUVMXv2bABM02TTpk29HWJEVVVVAZCcnMyUKb5Md2dJgfb26dOn99MIQzt69CitrVYRp6lTp3bar/3Yhx9+SF2dprGKiIiEa/LMewIbavZGJvAHgXGCriPxKrY+X0z6QuB+H/38B11HQvvkVwP3++r9mP7V0P0k0C35gft99X6MzA/dTwIlDAlum10GyRk9i5ecYZ3f0ZAQ15EbO1YOe5Z13S8ce5ZphoFIDNBfws7taXu9zzCMBNM0W9sPGIZhBz4DXAV+F43B9cauXbu824sXR6ag0uLFi9m5cycAu3fvZvXq1RGJGwntN//z8/MZ4vePf6hkwaVLlzh16hRw42TB888/z1e+8pUej2nPnj1dJmn86z+MGTOm037+x2pra8nKyurxuEREROJNa8sQEodct3YOboSJc4P6GN/oZtCDviepW1uGoEU/pE1sf77og59/6YbMiYH7ffV+dLyOhDb2bjj4Q99+X70fY/6020OLS8NHB+6PKwFHUVC3br0fjiIYNxtO7fS1DRvdaXcJobEWdi7s9HC3fz/Aijf2bkjN7vm4JKQevR8Sl+J+ZoFhGEMNw5hsGMYE/3bTNE8CbwDjgL/ucNpTwHDgZ6ZpXu6XgUaIx+PxFswFwi5o3BX/OAcPHsTj8UQkbiQcOHAACJ5B8Mc//jGovT2BMGTIEKZNm9ZpzGHDhjFy5Mgef9lsti7H7Xb71rJMSUnptJ//Mf9zREREpGtvH3/AtxTRqR1QU9m7gDWV3hsPpmnFl/gyoD5f2Mf7tv1+/lNTu1dnw9u/pjLwxpt/fLmxxA6fD/ri/Qh1HQnt5g5P/PfV+9HxOhLa9Q5/FvN9Dz32+P3oECfkdeTGdi2C61cCmlKTjE46hxbU//oVK65ERK9+PyRuDcpkgWEYcw3DeN4wjOeBlW3Nhe1thmF836/7GOAo8GaIUH8FnAeeNQzjl4ZhrDYM49fA32JND/5O330XfaO6utp7I9/hcJCZmRmRuFlZWTgcDsBKSFRXV0ckbiS0Jwv8Zwq8//773qLGoZIFU6ZMITk5udOYCxYs4MMPP+zx16c//em++FZFRESkm+557tXAhp0LockVsHRhOKZMmQJNrqAn7ILiy4A0aD9fLDoZuN/2879q1aqwbxikpqayatWqkD//QfHlxj6+JHA/0u9Hx/jSuVAzMCL9fnR2HQl2+aPAfYfvYcUevR/txnZ4ePJKh+tI5+qd8P7rgW2jC1m16rvdfD++G1xw+v3XrfjSa736/ZC4NViXIfoE8FiHtvFtXwDVQJcTcEzTPGkYRgHwXaAEmAOcBZ4FnjJNc8AtEN/U5CvYk5aWdoOe3We3273bzc3NEY3dUy6Xy1tw2T9Z0J4UGDlyJKNHjw5qj3a9Agj873nlypVO+/kf8z9HREREwlP5/kKKxpdhGFgfTl+dw7sHftu9tZCbXPDqHO+HW9O04hb3xYAlGj7BYP18ccufwPk/WNttP/8r/nobK1asCD9Gh59/b1zpnj/5e/jvDb79SL4f7fElPIk2sKWDx6/eeKTfD1u6ZnqE65rf+2B3QLLvoccVK1Z07/3wNyzLitdedNrj6vkY480f/k/gflvB6RXJGaz4yy/DwU1QvQs+OgQtfitPJNrgpmmQMwvyF1nnNf0NvDg98HfkD/8HZv4Q6Z1e/X5I3BqUMwtM01xlmqZxg69xfn1PdWzrEKvGNM2vmKY52jRNm2maOaZpLh+IiQIg4Gn5hoYeVqrvhP8SOElJSRGN3VPtSw11XFaoq+LGHdujITvbt0bfmTNnOu3nf8z/HBEREQlP8b8/h+vSLb6Gs/usD601leEFqKm0+p/d521yXbqF4n9/LoKjlGga1J8v/uL3gfsR+PkPGVe6lp4L4z8X2Bap92P856z4Er4pXwpui9T70Vl8CS0tx7dti+xDj9j8HrhLGxfZ2IPZe1sC92eXWUsIvTYffjwBfr8GzlUFJgrA2j9XZR3/8QT41UPWeR0LTneMLyL9ZlAmC6RzOTk53vXya2pquHTpUkTi1tXVUVNjZeNtNhs5OTldnNE/jh07Bljft38CI9QMgosXL3L06FEA/vRPb1xoqry8nFGjRvX467e//W2XY58yZQoJCdav6OHDhzvt135s1KhRKm4sIiLSQ5nfO8fVK8N9DfVO+EUxVJTAia1wtcN93Kt1VntFidXP72m4q1eGk/m9c/00cpEIWGEG7vfi5z9kPAnfrE0wpEO9st6+H0NSrLjSPZ3NxOjt+9FVfAk26i7ftieyDz3i8av7N+rOyMYerFo80OS3ZNO4Erh8Dp7PgxMVQId/A+wOGJFnvQYw4fgW67zL56yC0+2aPgpONIhIvxisyxBJJ2w2G9OmTaOqqgqAvXv3Mnfu3F7H3bt3r3c7Pz8/rAK+/eHChQuAVZDYX6gZBC+//DKmaTJ69OguZxZcvXqVc+d6fhMgnALQKSkpfOYzn+Gtt95ix44dfPOb3wzqY5omO3daRbLuu+++Ho9HREREYNj/auTSd0aSkXneWpIIrGKU7QUp7Q7rCUSP27dkgR/TtGYUKFEgA9IKE9Z2KDTZjZ//gDjSc6nZ1hO2r5cGH+vJ+wFWvFTNQO629pkeHddlb9fT9wM006O7Jn4Rfv1X1ra7BpouBSxF1GNX6wLfr4lf7H3MeHDpROB+6tjgv1njSqwC0o4Zge9V0yWo2QsHN1qFwwGaXdb5U58Ivs5NeREfvojcmGYWxKFZs2Z5tzdu3BiRmP5xZs6cGZGYkdBewPn48ePexMG5c+c4e/Ys4EsWOJ1OnnrqKQCWLVvmfaK/M48//jimafb4q6ioKKzxP/aYtTTunj17+K//+q+g45s3b+b9998H4NFHHw0rpoiIiHQu83vnqHx/IaZp3fwP4K6Bi+8G3Qhq71v5/kIlCmRgW2F2Xmugk59/r1v+RImCSJm8AIqfvXGfrt6PdsXPWvGkZ0LN9Agl3PcDNNOjJ5ouBu7X7A3dr7s+6BCn43UktEvHA/cP/9i3nT4eHq6Eedth4tzgpE5yptU+bzs8vCcwaXa4w/KNrg5JCRHpF0oWxKFFixZhtD0ut2PHDiorK3sVr7Ky0vt0u2EYLFq0qLdDjJj77ruPhIQEPB4P9913H2+99RZ/+INVwC0tLY3k5GR++MMfctddd3Hx4kXuuuuumCr+8thjjzFt2jRM02TevHm8+eabALS2trJ582a+9rWvAXD//ffz2c9+NppDFRERGTSK//05jG+YvHX0i7RcHxIycdDe1nJ9CG8d/SLGN0zVKJDB4S9+b930t4/vui9Y/VaYqlEQadOXwude6fn67LY06/zpSyM7rnjTPtMjkjTTo/s6LuV0MDIPPQbFaTgVmbiD3ZULfjt+M9JGF8IjVdZsgnA4iuCRA9Z5oeJdOd+LQYpIT2kZojiUm5vLvHnz2LLFKhizcOFCDhw4QEZGRrdjuVwuFi5c6N2fN28eubmxM51y0qRJ/PM//zPf/va3+eMf/8g999zjnTXgdrsZO3ast++CBQvYtGkTQ4cOjdZwgwwZMoTXXnuN4uJiTp06xcyZM0lJSaG1tZWmpibAmh3x0ksvRXmkIiIig889z73q3T62+zdc/PkzJNNIE6mM+NK3mDzzHhKBe6I3RJG+s+ikb/v4a7B7MVy/CkOGwcyNMOkL0RtbvJi8AMbeDXuWW+t6h2vSfChepxvSkTJ5gXXTcs+y3sfSTI/IOLXDKh7tKOp5jJpK3zJS0j0pN/vttD1NkZ4LD26D5IzuxUrOsM57cXpbUsjv6Yxht/RunCLSI4YZNL9a+kJBQYG5f//+sPsfPXqUKVOm9Nl4amtrycvLw+VyAVBYWMi2bdu6lTBwuVzMmTOHffv2AZCRkcGRI0fIzo69/yn97W9/y/r169m1axcXL1pTCw3DYOLEicyePZuFCxfyiU98IrqDvAG32833v/99Xn31VZxOJwkJCUyaNIkvfelLLF26NGZqRMSSvv4dEhER6U+GYVSZplkQ7XFIbOjuZwsZBOqdcHATVO+GC/8Nrdd8xxKGws0fh5yZkL9Ia+H3lWPlsGtRzwrs2tKspYeUKOiZj47AT6cGtqXnWk+ld/fmNECTy+/mtJ/HDmuN/HCc/yO80KHO48N7ep+8+UVxYNtfvAO3fKLnMUXkhjr7fKFkQT+JtWQBQHl5OaWlviI0ubm5lJWVhbWefmVlJQsXLsTp9P3j+sorr7BgQez/z8+4ceOorq7mJz/5CY8//ni0hyN9RMkCEREZTJQsEH9KFsS5Fg80VENLMyQmQVoOJOrhoX7RWKuZHtHQ4oEfJBPw1DlYy9d092n2Jhe8OgfO7utwwICvN+l3KRwdkzfjSqwaBL1VURI420PJG5E+1dnnC9UsiGMLFizg2Wd9hbOcTifFxcWUlJSwdetW6urqAvrX1dWxdetWSkpKKC4uDkgUPPvsswMiUVBfX8/p06cBKCjQ520RERERERlgEm2QORFummq96uZm/0nNhgc2w1ffhztXwsgCa2aHv4ShVvudK61+D2xWoqC3Em2QMjK4/ew+a4ZATWV4cWoqrf5BiQJg+Ej9LoXLbA3cz18cmbhBcfRws0g0qGZBnFu6dCm33HILS5Ys8S5JtHPnTm/BYofDgd1ux+12U1NTE3R+RkYGGzZsGBCJAoB33nkH0zRJTk5m8uTJ0R6OiIiIiIiIDDTpuXD3autLMz36x8S58N8brO2UkXDlnLVd77SWrxk327rZPHYGDMvynXe1Dj7YaxUz7lijIOUWXxHd2+b29XcweBgdnjsOt6BxV8Z2jGOE7CYifUvJAmHBggXcfffdLF++nIqKCvyXpgqVIABrvf958+axbt26mKxR0JkDBw4AkJ+fz5Ah+vEXERERERGRXmif6SF960/+3pcsuHIObnsQ/mcr3qfPT+30JQPsDrDZweMGd6h7Ggbc9kX4n1cD40t4/Gum2B2QnBmZuMOyrHjt75n/dUSk32gZIgEgOzubzZs3c/LkSVauXElBQUFQ0VybzUZBQQErV67k5MmTbN68eUAlCsCaWQBwxx13dNFTRERERERERGJCei6M/5xv/8I7VlHd1DHBfd01cPHd0ImC1DHWeRfe8bWN/5wKg3fHpRO+bVtaZGPb7H7X+Z/IxhaRsOjRagmQm5vL6tWrWb16NR6Ph+rqapqbm0lKSiInJycogTDQvPDCC7zwwgvRHoaIiIiIiIiIdMesTfDcJLh+2Vp+6K0nrSK4Hx2E33wLLhyE61eCzxuSAjfnwz3PwE35VoHj+rYajEOGW3ElfHXHfNuehsjG9rj9rnM0srFFJCxKFkinbDYbEydqOqWIiIiIiIiIRFlqNsx+Dl4vtfbbCxzPLoM/byta7GmE2n1wrRGGpkJ2IdhSrWM1lVb/9kQBWPFUgLp7Eof5tt010HQpMksRXa0LnA0yZHjvY4pItylZICIiIiIiIiIisW/yAqso8Z5l1n6oAsfjZvn6X62DE1tDFzguftaKJ92TlBG4X7PXKkDdWx/sDdyP9BJHIhIWJQtERERERERERGRgmL4UUm6BXYvBU2+1dafAsS0dZm1UoqCn7LcG7h/cGJlkwcGNgftpOb2PKSLdpgLHIiIiIiIiIiIycExeAF95FybNB4zAY50WODas/l95V4mC3jh/IHD/1A5riafeqKkMnvlxrqp3MUWkRzSzQEREREREREREBpbUbHhgs7UU0cFNUL3bKnbc4vH1SbRZRY1zZkL+IkjPjd54BwsjMbht50J45AAkZ3Q/XpPLOr+jxKHdjyUivaZkgYiIiIiIiIiIDEzpuXD3auurxQMN1dDSDIlJ1lI2ibZoj3BwSbnZb8cATCth8+oceHBb9xIGTS7rPG/R6bZ4AMkjIjFaEekmLUMkIiIiIiIiIiIDX6INMifCTVOtVyUKIu+2L/jtmL7Ns/vgxenhL0lUU2n1P7svdLyA64hIf1GyQERERERERERERLpmSw3cn/pV33a9E35RDBUlcGIrXK0L7Hu1zmqvKLH6eWcUAFOfuPF1RKRfaBkiERERERERERER6dpH7wbuN34An3sFdi+BZpfVdmqnr2Cx3QE2O3jcIYpOA0kZMHMDHPlJ8HVGfiLCgxeRrmhmgYiIiIiIiIiIiHTtw98H7p/aAcNHwuNHYNJ8rLoDftw1cPHdEIkCw+r/+BHr/PbkQrtzHa4jIv1CMwtERERERERERESkay2e4LadC+GRA/DAZmtpoYOboHo3fHQwsH+iDW7Kh5yZkL/IKk7d5LLO76j1Wp99CyLSOSULREREREREREREpGtpjuC2eie8Ogce3GYlAO5ebX21eKChGlqaITEJ0nICi043uazz/GsXtEsd22ffgoh0TssQiYiIiIiIiIiISNfScnzbySN822f3wYvToabS15Zog8yJcNNU69U/UVBTafU/uy90PP/riEi/UbJAOtXiacV1opmLh5pwnWimxdMa7SGJiIiIiIiIiEi0mH73hoaPguJnffv1TvhFMVSUwImtcLUu8NyrdVZ7RYnVz39GQfGzVu0C73XMvhl/PGvxwKUTcOGQ9RpqSSmJe1qGSAI0OD0c2VRHza5GLh5qptXj++OcYDMYMS0Jx6xU8hZlkZZru0EkEREREREREREZVK5e9G17GmD6Uki5BXYvgWaX1X5qp69gsd0BNjt43CGKHANJGTBzA0xeAPv/P7/rfNRX30F88daQ2AUfHQpRQ2Ia5Mzy1ZCQuKeZBQLA5dpr7Jh/mhcmHOfAmo+4UNUUkCgAaPWYXKhq4sCaj3hhwnF2PHSay7UqONMf3G43q1atYtq0aaSmppKens6f/MmfsHbtWjye3meCIxl/zZo1GIbh/RIRERERERGRQcJ/qSB3DTRdsm70P34EJs0HOtwHcNfAxXdDJAoMq//jR6zzr9YF9hl2U199B/GhsRZemw8/ngC/XwPnqoJnErR4rPbfr7H6/eoh6zyJa5pZIJwor2fvkjM0u4KXGUp1DMWWloCnoZXGGr/EgAkntzTwwe5GZmwYw8QF6f044vhSXV1NUVERp06dAiAlJYXm5mb279/P/v37eemll3jzzTfJzMyMevz33nuPp556qkfjEBEREREREZEYl2QP3K/ZCxPnQmo2PLDZ70n23fDRwRBPsudDzszgJ9k/2BsY15baZ9/CoHesPHCmR1hMOL7Fet/aZ3pIXNLMgjh3cP1F3iitCUgU3FqSyv1bb+WJuik8dvp2vnR4Io+dvp0n6qZw/9ZbubXE9we72dXKG6U1HFx/MVR46aWWlhYeeOABTp06xejRo9m1axeXL1/mypUrvPLKK9jtdt555x2+/OUvRz1+a2srTzzxBE1NTRQWFvZoPCIiIiIiIiISwzoWHj64MXA/PRfuXg2P/AGWumHhcXjskPW61G213706eMmbjnFU4LhnDqyH10u7mSjw0+yyzj+wPpKjkgFEyYI4dqK8nreWnfXup40fytzKXB7YPo7xc9NIzkwM6J+cmcj4uWk8sH0cc/eMIy13qPfYW8vOcqK8vt/GHi+ef/55Dh06BEBFRQUzZ84EICEhgQULFrBxo/WP6fbt23nzzTejGn/9+vW8/fbbfPnLX+a+++7r9lhEREREREREZIA5tQNqKkMfS7RB5kS4aar1mthJ7cuaSl+NA+m5Y+WwZ9mN+wwfBekTrNcb2bPMiidxR8mCOHW59hp7l5zx7o8qHMbDVbcxZsbwsM4fU5TKwwduY1ThMG/b3iVnYraGwZgxYzAMg5/97GfetkOHDnnX1a+v9yU6nn76aQzD4M4774zGUAP89Kc/BaC4uDjk0/qlpaXk5lrZeP/vrb/jO51OvvOd7zBixAj+9V//tdvjEBEREREREZEBoKE6uG3nQmhy9Sxek8s6P5zrSOcaa62lh0JJz7USBAk2uPwh1J+0XhNsVntnhY13L1ENgzikZEGcemv5We/SQ2m5Q/n8tnEkZSR2cVagpIxEPr/NN8Og2dXKW8vPdnFW/zt//jy1tdYftzvuuMPb/s477wAwfvx40tPTg9r9+0bDlStXePvttwG4//77Q/YxDIOSkhIA3njjjajF/9rXvsbly5f5l3/5F26++eZujUNEREREREREBgiP27dttN1WrHfCq3O6nzBoclnn1TsD4wF4GnszyvizZ3nw0kNDhgOG9d+3/iS0dihw3Oqx2uudVr8hKYHHm11WXIkrShbEoQanh5MVDd79e8vGdDtR0C4pI5F7y8Z4909WNNDg9NzgjP5XVVUFQHJyMlOmTPG2d5YUaG+fPn16P40wtKNHj9LaaiV0pk6d2mm/9mMffvghdXV1/R7/Rz/6EW+++SYzZ87k0UcfDfv6IiIiIiIiIjLAXPWrWZmU6ds+uw9enN75kkQd1VRa/c/uCx3v6kc9H2O8qXdaxYn9GYlw/TJgBrbbHTAiz3oNYML1K9Z5/o5v8SVzJC4oWRCHjmyq8/6tuLUklTFFvaswP6YolVtnt8Uw2+LHkPab//n5+QwZMiSo3T9ZcOnSJU6dOgXcOFnw/PPPe5cw6slXZWVll+Nunw0B1jJKnfE/5n9Of8Q/c+YM3/zmNxk2bJi3voGIiIiIiIiIDFLJI3zbTRfh7jW+/Xon/KIYKkrgxFa42uH+0NU6q72ixOrnfxP6T1db8doNu6lvxj8YHdwU3Ga2+LbHlcAXtsJf18Gi0/D4Yev1r+us9nEloc+7UXwZtIZ03UUGm5pdvqlceYuzIhIzb3EWp3dacT/YfRlWRyRsRBw4cAAInkHwxz/+Mai9PYEwZMgQpk2b1mnMYcOGMXLkyB6PyWbrpKiPH7fbN7UvJSWl037+x/zP6Y/4ixcvpr6+nmeeeYbx48eHfW0RERERERERGYCS7IH7mbfD516x1rdvXwbn1E5fwWK7A2x2a/kid02IeBkwc0Nw8WNb7x5sjSvv/0fo9vTxMLsMHDNCH0/OhIlzra+aSqt2RKhZBO+/DnfH0I0+6VNKFsSZFk8rFw81e/ezwyxo3JXsGb4byh8dbKLF00qiLTYmrrQnC/xnCrz//vveosahkgVTpkwhOTm505gLFixgwYIFfTHcAePFF1/k9ddf5xOf+AR/93d/F+3hiIiIiIiIiEhfS8vBWqjEWtaYgxth3nYYe7e1vv3xCgKWvgmVIADAgEnzoHgdpGZbsw28EtquI11q8cDFd4PbRxfCg9sgOSO8OI4ieOSAVUPCf2kogItHrOt0TOjIoBQbd3Ol37irr9Hqsf5opzqGkpzZs1oFHSVnDSHVYRU6bvWYuKuvRSRub7lcLpxOKyvqnyxoTwqMHDmS0aNHB7VHu14BgN3uy9ZfuXKl037+x/zP6cv458+f5+tf/zqJiYn86Ec/CljeSUREREREREQGqUQbJPutUnFqh/VUemo2PLAZvnoS7lwJIwuCby4n2qz2O1da/R7YbJ1XU+mbiQBWfN2YDk9DNZitgW3pud1LFLRLzrDOS88NbDdbretIXNAdvjjT0uTL7trSIpsrGmr3xWtpNm/Qs/+0LzXUcVmhroobd2yPhuzsbO/2mTNnyM/PD9nvzJkzIc/py/jf+ta3uHjxIn/5l3/J5MmTaWxsDDjH4/EVuW4/ZrPZwlp+SURERERERERiWEKH24k7F1pPpSdnWDea715tfbV4rJvMLc2QmGTNFuiYBGhyWef7S9TtyrA1h1iOenZZ9xMF7ZIzrPN/URzY7mkM2V0GH80siDOJyYZ329PQeoOe3XfN7YuXmGTcoGf/OXbsGAA5OTkkJSV520PNILh48SJHjx4F4E//9E9vGLe8vJxRo0b1+Ou3v/1tl2OfMmUKCQnWr+jhw4c77dd+bNSoUWRlhV+Dojfx22dr/PCHP8Rutwd9rV7tW8uuve3v//7vwx6biIiIiIiIiMSgFg80dShcXO+0lq9pcgW2J9ogcyLcNNV6DZUoeHVO8Dr5V+us60jX/ItCg1Ws2FHUu5iOIhg3O7Dt6ke9iykDhpIFccaeM5QEm3Ujv7HmGk2XQlQ574Gmuus01lhLDyXYDOw5QyMSt7cuXLgAWAWJ/YWaQfDyyy9jmiajR4/ucmbB1atXOXfuXI+//J+870xKSgqf+cxnANixY0fIPqZpsnOnNVXvvvvu6zJmf8YXERERERERkUGmoRpa2+5pJI/wtZ/dBy9Ot5YUCkdNpdXff3389nitHi17E65hIwL38xdHJm7HOMNuikxciXlKFsSZRFsCI6b5nrCv3Xs5InFr9/rWtb8pPzlmihtnZmYCcPz4cW/i4Ny5c5w9exbwJQucTidPPfUUAMuWLfM+cd+Zxx9/HNM0e/xVVFQU1vgfe+wxAPbs2cN//dd/BR3fvHkz77//PgCPPvpoWDEjEb+ysvKG398//dM/efu2t/3gBz/o9vhEREREREREJIZcb/JtDx8Fxc/69uud1vI1FSVwYqs1Q8Df1TqrvaLE6uc/o6D4WRg+0rff0tw34x9sEpMC9x0zIhN3bIc4qiERN2Ljjq70K8esVO/2kY11N+gZPv84Y2cOj0jMSLjvvvtISEjA4/Fw33338dZbb/GHP/wBgLS0NJKTk/nhD3/IXXfdxcWLF7nrrrtYsWJFlEft89hjjzFt2jRM02TevHm8+eabALS2trJ582a+9rWvAXD//ffz2c9+Nuj8559/HsMwMAyDysrKiMcXERERERERkTgyJNm37WmA6Uvhc69AUoav/dROeO1B+PcRsOlWeD7Pev33EVa7fzHjpAzr/OlLweO3/n7Hm+DSNbsDkjMjE2tYlhVP4o4qhsShvEVZHHjmIzDh9I5GzlQ2MqYotesTO3GmspHTO9sKnRhW/FgxadIk/vmf/5lvf/vb/PGPf+See+7xzhpwu92MHTvW23fBggVs2rSJoUNjYwklsAozv/baaxQXF3Pq1ClmzpxJSkoKra2tNDVZ2fw77riDl156KSbji4iIiIiIiMgg0l6kuMUD7hpougSTF8DYu2HPcjheAZi+/u6aTgIZMGkeFK+D1Gxr1kF730SbdR3pmulXj9SWFtnYNrv/hSIbW2KWZhbEobRcGxPm+f6A/HrhGZpdPatd0Oxq4dcLz3j3J8xLIy03tqYmPfnkk7z99tuUlpYyYsQIWlt9f0gnTZrE0qVLeeedd3jllVdIS4vwH9YIGDduHAcPHuQf//EfmTp1KoZhMHToUD75yU/y/e9/n9/97nfe5ZZiMb6IiIiIiIiIDBKJNrhpmm+/Zq/1mpoND2yGr56EO1fCyILgpWsSbVb7nSutfg9sts4D+GCvr99N+Vr2JlyG361dT0NkY/vP9MCIbGyJWYZpKjPUHwoKCsz9+/eH3f/o0aNMmTKlz8ZzufYaP887QbPLunE+qnAYn982jqSMxLBjNLta+I85p/hw31UAkjIS+NKRiQzPjp0n80MZN24c1dXV/OQnP+Hxxx+P9nCkj/T175CIiEh/MgyjyjTNgmiPQ2JDdz9biIiIRNRbT8Lv11jb40pg3vbQ/VraChW3NFvLCrXPSgilosS3PNGdK+Hu1ZEf92D00RH46VTf/l/XRWYpoqt11rJR7R47DDfl9T6uxIzOPl9oZkGcGp49lBkbxnj3P9x3lV9M/x/OVDaGdf6ZykZ+Mf1/vIkCgBkbxsR8oqC+vp7Tp08DUFCgz9siIiIiIiIiIt2Svwjvk+andkBNZeh+iTbInAg3TbVeO0sU1FT61TEw2uJLWPyXIQLfTI/e+qBjHD1sHi+ULIhjExekc/ezo737Dc5r/LL4FL8qOcX7Wxtoqrse0L+p7jrvb23gVyWn+GXxKRqc17zH7n52NBMXpPfb2HvqnXfewTRNkpOTmTx5crSHIyIiIiIiIiIysKTnWvUG2u1cCE2unsVqclnnt5s0z4ov4fEvOA1wcGNk4naMo4LTcUMFjuNc/tIRDLtlCHuXnPEuSXR6p69gcapjKEPtCVxzt9JYcy3o/KSMBGZsGDMgEgUABw4cACA/P58hQ/TjLyIiIiIiIiLSbcXroHo3NLug3gmvzoEHt0FyRvgxmlzWefVOaz8pw4or4UvLgYSh0Np2z659poejqOcxayr9ZnpgxVfB6bihmQXCxAXpfOnIRCbMTwuqV9JYc41L7zYHJwoMmDA/jS8dmThgEgVgzSwAuOOOO6I8EhERERERERGRASo1G2Zu8O2f3QcvTu98SaKOaiqt/mf3+dpmbvAVPJbwJNrg5vzAtkjO9AC4+eMqOB1H9Gi1AFYNg5LNt9Lg9HBkUx0f7L7MRwebaPX41iRLsBnclJ/M2JnDyVuURVruwPtD8cILL/DCCy9EexgiIiIiIiIiIgPb5AVw5TzsWWbt1zvhF8UwbjbkL4axM2BYlq//1TprLfyDGwOfXAcoftaKJ92XMwvOVfn2IzXTwxt/ZiRGKQOEkgUSIC3XRuHqUbAaWjytuKuv0dJskphkYM8ZSqJNk1FERERERERERASYvhRSboHdS6wlicBKBLQnA+wOsNnB4wZ3TfD5SRnWjAIlCnoufxH8/hkCihC3z/SYXRbekkQ1ldaMgo6JAhWcjjtKFkinEm0JZExUARMREREREREREenE5AUw9m7YsxyOVxBw0zpUggAAwypmXLxOSw/1VnvB6eNbAtt7M9OjnQpOxx0lC0RERERERERERKTnUrPhgc3WDeqDm6zixx8dhBaPr0+iDW7Kt5a1yV+km9CR5F9wGsBIBLPF2vaf6TF8FAxJgetX4PKHwXH8z1PB6bikZIGIiIiIiIiIiIj0Xnou3L3a+mrxQEM1tDRDYhKk5ahQbl9pLzj9eqm1b7b4kgL+QiUI2nXsr4LTcUnJAhEREZEI8Xg8VFdX09TURHJyMjk5Odhs+kAkIiIiInEo0QaZE6M9ivjRseB0x0RBV/z7q+B03FKyQERERKQXnE4nmzZtYteuXRw6dAiPxzfV2mazMW3aNGbNmsWiRYvIzdVUaxERERER6SPTl4Lrf+Cd9QTUjmg3fBQMGQ7XL3cyy8CAO5ZacSQuJUR7ACIiIiIDUW1tLfPnz2fChAmsWbOGqqqqgEQBWDMNqqqqWLNmDRMmTOChhx6itrY2SiMWEREREZFB7cB6eOdZAhIF6bmQPgESbFaCoP6k9Zpgs9oDakeY1vkH1vf3yCVGKFkgIiIi0k3l5eXk5eVRUVGBaQY+seNwOMjLy8PhcAS0m6bJli1byMvLo7y8vD+HKyIiIiIig92xct8SRGDNIMCwik7Xn4TWwAebaPVY7fVOq9+QFN+xPcuseBJ3lCwQERER6Yb169dTWlqKy+XytpWUlLB161bq6uo4ffo0hw8f5vTp09TV1bF161ZKSkq8fV0uF6Wlpaxfr6d1REREREQkAhprYfcS376RaC011HEpIrsDRuRZrwFMq2aBkehr2r3EiitxRTULRERERMJUXl7OsmW+p3XGjx9PWVkZM2bMCNk/MzOTuXPnMnfuXCorK1m4cCFOpxOAZcuWccstt7BggQqHiYiIiIhIL+xZDs0u377Z4tseVwL5i8ExA5Izfe1Nl6BmLxzcCKd2BJ/X7LLiPrC5L0cuMUYzC0RERETCUFtby5Ilvqd1CgsLqaqq6jRR0FFRUREHDhygsLDQ27ZkyRLVMBARERERkZ6rd8LxiuD29PHwcCXM2w4T5wYmCsDanzjXOv7wng61C9ocr2hbpkjihZIFIiIiImFYvny5d+mh3Nxctm3bRkZGRrdiZGRksG3bNnJzrf8Rd7lcLF++PMIjFRERERGRuHFwE0HLDY0uhEeqrNkE4XAUwSMHrPMCmG3xJV4oWSAiIiLSBafTSUWF72mdsrKybicK2mVkZFBWVubdr6io8C5NJCIiIiIi0i3VuwL303PhwW2QnNG9OMkZ1nkdZxhU7+7N6GSAUbJAOtfigUsn4MIh67XF0/U5IiIig9CmTZswTetpnZKSEoqKinoVr6ioiNmzZwNgmiabNulpHRERERER6aYWD1w4GNg2u6z7iYJ2yRnW+f4u/LfuCcYRFTiWQPVOa3pR9S746FDgH4NEG9w0DXJmQf6i0GuZiYiIDEK7dvme1lm8eHGn/TweD9XV1TQ1NZGcnExOTg42my1k38WLF7Nz504Adu/ezerVqyM7aBERERERGdwaqqH1mm9/XIm1pFBvOIpg3Gw4ZX1WofWadZ3Mib2LKwOCkgViaayFXy+DE68StM5ZuxYPnKuyvn7/DEyaB8XrIDW7X4cqIiLSnzweD4cOHfLudyxo7HQ62bRpE7t27eLQoUN4PL5Eu81mY9q0acyaNYtFixZ5axV0jHPw4EE8Hk+niQUREREREZEg15sC9/M7f7CpW/IX+5IFAC3NkYkrMU/LEAkcK4fn8+BEBUGJArsDRuRZrwFMOL7FOu9YeX+NNG653W5WrVrFtGnTSE1NJT09nT/5kz9h7dq1ATelYiH+mjVrMAzD+9WVt99+m9LSUhwOB0lJSdx8883ce++9/PSnP/Uu+SEiEk3V1dXev4UOh4PMzEwAamtrmT9/PhMmTGDNmjVUVVUF/c30eDxUVVWxZs0aJkyYwEMPPURtbS0AWVlZOBwOb7/q6up+/K5ERERERGTAMzrc2g23oHFXxnaM0/X9HRkcNLMg3h1YD3uWBbaNK7EyiI4ZkJzpa2+6BDV74eBGOLXDamt2weulcOU8TF/ab8OOJ9XV1RQVFXHq1CkAUlJSaG5uZv/+/ezfv5+XXnqJN99803vzKprx33vvPZ566qmwr/0P//APfO973/PuZ2Rk0NDQwJ49e9izZw+vvPIKv/zlL0lKSur29yUiEilNTb6nddLS0gAoLy9nyZIluFyuoP4Oh4O0tDQaGhqoqanxtpumyZYtW9i9ezcbNmxgwYIF2O127/HmZj2tIyIiIiIiPWR3BN7H641hWVY8d03XfWVQ0cyCeHasPDBRkD4eHq6Eedth4tzgPzDJmVb7vO3w8J7AmgV7lmmGQR9oaWnhgQce4NSpU4wePZpdu3Zx+fJlrly5wiuvvILdbuedd97hy1/+ctTjt7a28sQTT9DU1ERhYWGX/X/84x97EwWlpaXU1NRw6dIl3G43L774Ina7nR07drB0qZJQIhJdycnJ3u2GhgbWr19PaWlpQKKgpKSErVu3UldXx+nTpzl8+DCnT5+mrq6OrVu3UlJS4u3rcrkoLS1l/fr1uN1ub7sSoyIiIiIi0i1mq2/blnbjvi0euHQCLhyyXrsqWmyz++1o5Yd4YWiZj/5RUFBg7t+/P+z+R48eZcqUKX03oMZaawmhZpe1P7oQHtzWvWrpTS54dQ6c3WftJ2XA40dUwyCCnnvuOb761a8C8Nvf/jboJvzPf/5z/vzP/xywimN+9rOfjVr8devW8fWvf50vf/nL3Hbbbd4ZBqH+xrS0tDB27Fg+/PBDpk+fzv79+4OWLHr++ef5yle+QkJCAn/84x+ZNm1at763Pv8dEpG4UVdXx4gRI0IeGz9+PGVlZUF1DEKprKxk4cKFOJ3OkMcvXrxIVlZWr8Yqg5dhGFWmaRZEexwSG7r72UJEREQGqY+OwE+nWtt2Byw6HXi83gkHN0H1LvjoUGCCINEGN02DnFmQvyjwoWCATbf6ZhY8dhhuyuu770P6XWefLzSzIF7tWe5LFKTndj9RAFb/B7f5/pg0u6y4MWjMmDEYhsHPfvYzb9uhQ4e86+rX19d7259++mkMw+DOO++MxlAD/PSnPwWguLg45NP6paWl3mKZ/t9bf8d3Op185zvfYcSIEfzrv/5rl9fdv38/H374IQArVqwIWdvgscceY+TIkbS2tnrHKSISDVVVVSHbCwsLqaqqCitRAFBUVMSBAwc6nX3V2XVERERERES65K6xlhAH6yHh1+bDjyfA79fAuargmQQtHqv992usfr96yDoP4GqdliCKU0oWxKN6Jxyv8O3PLut+oqBdcoZ1frvjFVb8GHL+/HlvMck77rjD2/7OO+8A1lOh6enpQe3+faPhypUrvP322wDcf//9IfsYhuFd2uKNN96IWvyvfe1rXL58mX/5l3/h5ptv7vLa/kU8P/axj3V67dtvvx2AHTt2dBlTRKSvNDQ0BLXl5uaybds2MjIyuhUrIyODbdu2eROx/hobG3s6RBERERERiUf+yxCBVWv0WLm1msiJCoKWD7I7YESe9RoYCI5vsc47Vg4f7A0+LnFBBY7j0cFNeH/Jx5WAo6h38RxFMG42nNppxT24Ce5e3buYEdT+pGZycnLAsjSdJQXa26dPn95PIwzt6NGjtLZaf/SnTp3aab/2Yx9++CF1dXVhL2ERqfg/+tGPePPNN5k5cyaPPvpoWNf219LS0uWx9957D4/Hg81m63Z8EZHeGjZsWFBbWVlZtxMF7TIyMigrK6O4uDigXTULRERERESkW4wOz4H/57eh7mhg27gSyF8MjhmB9UmbLlnJhYMb4VTbQ5rNLni9FLImd7xQpEcuMUozC+JR9S7fdv7iyMT0j1O9OzIxI6T95n9+fj5DhgwJavdPFly6dIlTp04BN04WPP/8894ljHryVVlZ2eW422dDgLWMUmf8j/mf0x/xz5w5wze/+U2GDRvGxo0bw772uHHjvNuHDx8O2ef69eu899573u0LFy6EHV9EJJKyswNr8ZSUlFBUVATA2rVrsdvtYf3tt9vtrF27FrCWJJo9e/YNryMiIiIiItIt/omC9PHwcCXM2w4T5wYmCsDanzjXOv7wnsCaBXXH+mGwEouULIg3LR6roEk7R3jrLHdprF+cjw52XVG9Hx04cAAInkHwxz/+Mai9PYEwZMiQGxbUHTZsGCNHjuzxVzhPyLvdbu92SkpKp/38j/mf0x/xFy9eTH19PatWrWL8+PFhX/uTn/wko0aNAuCZZ57h+vXrQX02btzIRx995N0PtQyIiEh/SExMDNhfvNiXIF+1alXYywc1NjayatWqkHGAgIS2iIiIiIhIlzouQ9RudCE8UhX+fT9HETxywDov9IV6MjoZgPSpNN40VPtu5NsdwVnFnhqWZcVz11jxG6ohc2JkYvdSe7LAf6bA+++/7y1qHCpZMGXKFJKTkzuNuWDBAhYsWNAXwx0wXnzxRV5//XU+8YlP8Hd/93fdOjcxMZFVq1axZMkSjh49yuc+9zn+9//+30ybNo1Lly7x8ssv8+STTzJ06FCuXbsGQEKCcpsiEh0d//74FzTubp0B//4dCyOHKvYuIiIiIiLSqSEh7l2l58KD27pfnzQ5wzrvxenB9UgTtWRqvNDdt3hzvcm3bUuLbGyb3bfd0hzZ2D3kcrlwOq0/cP7JgvakwMiRIxk9enRQe7TrFQDY7b7/nleuXOm0n/8x/3P6Mv758+f5+te/TmJiIj/60Y969DTs4sWLWblyJWAVTy4oKCApKYlRo0bxd3/3d2RkZPDtb3/b2z8zM0KJLRGRXnA4HBH7e5SVlYXD0bGwmIiIiIiISJjScsDocE9mdln3EwXtkjOs8/0ZQ6zrSFxQsiDe+GccPRFe1sXjt0RNjGQc25ca6risUFfFjTu2R4P/2tVnzpzptJ//se6sd92b+N/61re4ePEiixYtYvLkyTQ2NgZ8eTy+ZahCtbVbvXo1v/vd73jiiSeYNm0aDoeDT37yk3z729/m8OHD3mKfmZmZ3HzzzWF/byIikdReDB4gLS2yiXb/xK1pamqviIiIiIh0Q6ItMDEwrsRaUqg3HEUwzq++WnKmdR2JC1qGKN6k5Vi/4C0ea8mgpkuRWYroap0VD6z4MZJxPHbMKsiSk5PjvfEMoWcQXLx4kaNHrUIwf/qnf3rDuOXl5SxfvrzH43r11Vf59Kc/fcM+U6ZMISEhgdbWVg4fPsz9998fsl97geBRo0aRlZUV9hh6E799tsYPf/hDfvjDH97wOu03wpYvX84PfvCDoON33XUXd911V8hzf/Ob3wBQWFio5TlEJGr8l6WLdP0U/1ow/v9OiYiIiIiIhOX6Vd92/uLO+3VH/mI4tbMtfuerUcjgo5kF8SbRBjf5Fe6t2RuZuB/4xbkpP2YyjhcuXACsgsT+Qs0gePnllzFNk9GjR3c5s+Dq1aucO3eux1+hnrLvKCUlhc985jMA7NixI2Qf0zTZudP6433fffd1GbM/4/fW6dOn2bVrFwCPPfZYv15bRMRfTk6OtzB9TU0Nly5dikjcuro6amqsRLvNZiMnJzYS7SIiIiIiMkC0eOCa3838cAsad2WsX5xrV3z1T2XQU7IgHuXM8m0f3BiZmP5xcmZGJmYEtK8rffz4cW/i4Ny5c5w9exbwJQucTidPPfUUAMuWLeuymO7jjz+OaZo9/ioqKgpr/O03yffs2cN//dd/BR3fvHkz77//PgCPPvpoWDEjEb+ysvKG398//dM/efu2t4WaVdCZa9eusWjRIlpaWpg6dSpf/OIXu/29iYhEis1mC1jKbu/eyCTa/ePk5+d7ExIiIiIiIiJhuXQCaFvO1O6IzOohAMOyrHhgxb90IjJxJeYpWRCP8hcBbUu6nNoBNZW9i1dT6ZuahNEWPzbcd999JCQk4PF4uO+++3jrrbf4wx/+AFjrTicnJ/PDH/6Qu+66i4sXL3LXXXexYsWKKI/a57HHHmPatGmYpsm8efN48803AWv97M2bN/O1r30NgPvvv5/PfvazQec///zzGIaBYRhUVlZGPH5vvP/++/zDP/wDBw4coKnJKrzd0tLC3r17uffee9m5cyepqan87Gc/Y+jQoRG9tohId82a5Uu0b9wYmUS7f5yZM2Mn0S4iIiIiIgNEvdO3bYtsfTVsvvpqNJyKbGyJWUoWxKP0XJg0z7e/cyE0uXoWq8llnd9u0jwrfoyYNGkS//zP/wxYxY7vuece/uzP/gyw1okeO3Ysf/VXf8WFCxdYsGABb7zxRkzdmB4yZAivvfYa48aN48yZM8ycOZPhw4czfPhwHn74YRoaGrjjjjt46aWXYjL+jTQ0NPC9732PT37yk6SkpJCVlUVycjJFRUX853/+J9nZ2bzxxhsxUWxaRGTRokXe2ik7duygsrKSy7XXehTrcu01Kisrvcu8GYbBokWxk2gXEREREZEByBPZ+mp43F33kUFHyYJ4VbwOkjKs7XonvDqn+wmDJpd1XnsWMynDihtjnnzySd5++21KS0sZMWIEra2t3mOTJk1i6dKlvPPOO7zyyiukpUU4CxsB48aN4+DBg/zjP/4jU6dOxTAMhg4dyic/+Um+//3v87vf/c673FIsxr/Rdf/xH/+Re+65h9GjR3P58mXS09MpLCzkmWee4b333qOwsDDi1xUR6Ync3FzmzfMl2p95uIyXJr/Xo1gvTX6PZx4u8+7PmzeP3NzYSbSLiIiIiMgA4f/ArrsGmiJTX42rdVa8dmnjIhNXYp5hmma0xxAXCgoKzP3794fd/+jRo0yZMqUPRwQcK4fXS3376bkwuwwcRV2fW1NpzSjwn+70uVdg8oIIDzLyxo0bR3V1NT/5yU94/PHHoz0c6SP98jskInGltraWvLw8Pu6aw0M8CcAK7qKZK12c6ZNECmuxasRsZjX/nbGNI0eOkJ2d3SdjlsHDMIwq0zQLoj0OiQ3d/WwhIiIig1SLB36Q5Nv/wlaYOLf3cU9shdce9O1/vRkSVWNtMOns84VmFsSzyQug+Fnffr0TflEMFSXWH4WrdYH9r9ZZ7RUlVj//REHxswMiUVBfX8/p06cBKCjQ520REQlfdnY26x592ZsoAJjDX5FESljnJ5HCHP7Ku/8QT7Lu0ZeVKBARERERkcg4GJn6ahGLIwPOkGgPQKJs+lJIuQV2L4Fml9V2aqevYLHdYRU08bgDpx+1S8qAmRsGRKIA4J133sE0TZKTk5k8eXK0hyMiIgPI5dprXP3xrYBvVuYXx3+V9WWrGDNjeJfnn6ls5NcLz9Dg9NU6uPrjW7n8rWsMz46dejkiIiIiIjJANFQH7p/aYa0GEs6qIZ2pqfTdF/S/TubEnseUAUMzC8S60f/4EZg0HzACj7lr4OK7IRIFhtX/8SMDJlEAcODAAQDy8/MZMkS5MhERCd+eRWe4fsWXKBhVOIyHq24LK1EAMKYolYcP3MaowmHetutXTPYsOhPxsYqIiIiISBy43hTctnNh9+uStmtyWed31NLcs3gy4ChZIJbUbHhgM3z1JNy5EkYWBK9Flmiz2u9cafV7YLN13gDyzjvvAHDHHXdEeSQiIjKQNDg9VL/e6N1Pyx3K57eNIykjsVtxkjIS+fy2caTl+mYSVL/eSIPTE7GxioiIiIhInDBC3Nqtd8Krc7qfMGhyWef5Lzvuu1APBicDkR6tlkDpuXD3auurxWNNM2pphsQkSMsZ8MVMXnjhBV544YVoD0NERAaYA//nQsD+vWVjup0oaJeUkci9ZWP4ZfGpgPhFPxzTmyGKiIiIiEi8abkWuv3sPnhxOswuC29JoppKa0ZByETBDa4jg45mFkjnEm3WemQ3TbVeB3iiQEREpKfe/2WDd/vWklTGFKX2Kt6YolRune2L4fylu1fxREREREQkDjV+4Nu2O6D4Wd9+vRN+UQwVJXBiK1ytCzz3ap3VXlFi9fNPFBQ/a8Vrd1lLp8YLzSwQERERuYEWTytXz7V49/MWZ0Ukbt7iLE7vtJY2unLuOi2eVhJteo5DRERERETC1Or3xL8tDaYvhZRbYPcSaHZZ7ad2+goW2x1gs4PHHaI+KZCUATM3WPVJD27wtWtmQdxQskBERETkBlwnPOCra0x2mAWNu5I9I8W3Y1rXGZGXHJHYIiIiIiISBxKTfNuettnQkxdYK4T88gvQ2GFGQKgEQbvUMTD3NRg5vS2e3+xnrTYSN/T4moiIiMgNuP2KD6c6hpKc2bNaBR0lZw0h1eErdOw+pSLHIiIiIiLSDSmjfNvuGmi6BMfKYfNngxMFXWk8Y513rNxaosg/sTB8dGTGKzFPMwtEREREbsBvUgG2tMg+ZzHUruc2RERERESkh5Lsgft7/x4O/ziwbVwJ5C+G7EJr9kFLszUjwZYGtfvg4EY4tcPq2+yC10th6hOBMWy9q9kmA4eSBTHMNE0Mw4j2MEQGHNM0u+4kIhKmtFzf0/+ehtaIxr7m9sWzjxt6g54iIiIiIiIdpOVgLRzT9rnCP1GQPh5ml4Fjhq9t+MjA8yfOtb5qKmHnQl+R48PP+XVKaLuOxAM9zhajEhMTaWlp6bqjiARpaWkhMTEyy4SIiGRM9K0D2lhzjaZLkfn3uanuOo01vkJh/tcRERERERHpUqINbvpYcPvoQnikKjBRcCOOInjkgHVeRzflqWZBHBnUyQLDMMYahlFmGEatYRjNhmGcMgzjB4ZhZHYzzucMw3jDMIwPDMO4ahjG+4ZhbDYMI8RvUGSkpKTQ2NjYV+FFBrXGxkZSUlK67igiEoZEWwKG31zM2r2XIxK3du8V73bCEOs6IhK7BvJnCxERERnExn8+cD89Fx7cBskZ3YuTnGGdl57bIf7nejM6GWAG7adSwzAmAFXAV4DfA/8KvA8sB/YZhjEizDjPAP8BTAd2AOuAA8CfAW8bhvFI5EcPaWlp1NXVaXaBSDe1tLRQV1dHWlpatIciIoNEi6cV02/1oSMb67zba9euxW63YxhGl192u521a9eGjNPaal1HRGLTQP9sISIiIoNY7v2B+7PLup8oaJecYZ1/o/gyqA3aZAHw78AtwDLTNOeaprnSNM17sf7H/nbge10FMAxjFPAN4BzwMdM0v9oWZz4wGzCA7/bF4O12O8OHD6e6uhqXy8X169e1DrtIJ0zT5Pr167hcLqqrqxk+fDh2u73rE0VEwuCuvuZdAhTg9I5GzlRas/9WrVoV9kzAxsZGVq1aBcCZykZO7/Q7r7XtOiISqwb0ZwsREREZxJzbfdvjSqwlhXrDUQTjZoeOL4PeoCxwbBjGeOA+4BTwbx0O/xOwCPgLwzBWmKZ5o7UE2quE/Jdpmuf9D5imuccwDDdwc8QG7scwDG655RbcbjcNDQ2cP39eswxEbiAxMZGUlBRuuukm71O+IiKR0NIUnKz/9cIzPHzgtm4vGdjY2Eizq4VfLzwTfJ1mPRQgEosGw2cLERERGcSqd/m28xdHJmb+Yji1sy3+brh7dWTiSswblMkC4N621zdM0wyY02+aptswjLex/of/U8CbN4hzAvAAdxqGcZNpmh+1HzAM4x7ADvwykgP3ZxgGaWlpWk5FREQkihKTg5OPDc5r/MecUwFt/5dDncb4G6Z5t/9jzikanMGzCBKTlOQUiVGD4rOFiIiIDEItHvjI73NIuAWNuzLWL85HB63rqMhxXBisyxDd3vZ6vJPjJ9peJ90oiGmadcC3gJHAu4ZhbDIMY7VhGL8A3gB2ARFK2YmIiEgssucMtRYH6aDhSHWP4oU8z2i7jojEIn22EBERkdjUUG3dyAewOyA5MzJxh2VZ8cCK39Czzz4y8AzWZEF622t9J8fb2zO6CmSa5g+AB7FmYXwNWAk8BNQAz3ecQuzPMIxFhmHsNwxj/4ULF8IbuYiIiMS0T60ZyW0f38Gff/PPenT+n3/zz7jt4zv41OpbIjwyEekj+mwhIiIisel6k2/b1sXKJC0euHQCLhyyXtuTDJ2x+dWCbGnu+RhlQBmsyxB1pf35wC4XBzYM4++B/w08C/xf4ENgMrAaeMkwjE+Ypvn3oc41TXMTsAmgoKBACxGLiIgMQO7qa97/Y0h1DOWTs16BId/scbykYY3M/otvQnESh//9PhprrPju6mtkTEyK0KhFpB/ps4WIiIhEx5Bk37anIfh4vRMObrLqGnx0KDBBkGiDm6ZBzizIXwTpuYHnetx+ffU5JV4M1pkF7U/3pHdyPK1Dv5AMwygCngFeM03z70zTfN80zSumaR4AvgicAVa0FT0TERGRQci/wPFtH98Oe5ZFJvCeZUzI3+67jgoci8QqfbYQERGR2JSW46sl4K6BpkvWdmMtvDYffjwBfr8GzlUFzyRo8Vjtv19j9fvVQ9Z5AFfrrHhgxU/L6Z/vR6JusCYL3mt77Wzd0Iltr52tO9ru822vezoeME3zCvB7rP+Gd3R3gCIiIjIwtBc4Tkk7z52f+bbvwOjCngX0O++uP/02KWnWqiMqcCwSs/TZQkRERGJT++yAdjV74Vg5PJ8HJyoImvhod8CIPF89Ai8Tjm+xzjtWDh/s9R26KV/FjePIYF2GqP1/wO8zDCPBNM3W9gOGYdiBzwBXgd91Ead9js3NnRxvb+9ikS8REREZqNoLHBfNf4qhQ69ajem58OA2oAcFxB7cBi9Oh3onQ4depWj+U2z7yb+pwLFI7NJnCxEREYldObOsGQIA//ltqDsaeHxcCeQvBseMwALITZes5MLBjXBqh9XW7ILXSyFrsl/8mX06fIktg3JmgWmaJ4E3gHHAX3c4/BQwHPiZaZqXAQzDGGoYxmTDMCZ06PtW2+siwzDG+B8wDON+rA8GTcBvI/sdiIiISCyxZ37AuCm/8TXMLoPkjIA+f8O0Tr8CJGdY57cZN+U32DM/6LvBi0iv6LOFiIiIxLT8RXhLKPknCtLHw8OVMG87TJwbmCgAa3/iXOv4w3sCaxbUHWvbMNriS7wYrDMLAP4K63+0nzUM47PAUeAuoBhrivB3/PqOaTtejfUhoN0WYDcwEzhqGMZWrCJkU7CmERvAStM0L/bpdyIiIoOGx+OhurqapqYmkpOTycnJwWbTlM5Y5q6+xh1FP8FoXyVoXAk4inoX1FEE42bDqZ0YBtxR9BPc1cUqcCwSu/TZQkRERGJTei6MnwPvv+5rG11ozWju8IBTpxxF8MgBeHUOnN3nax8/J7jwsQxqg3JmAXifACoAnsf6H/kVwATgWaAwnP8Jb5tiPAf4W+BdrMJjK4BPAduA2aZpruuL8YuIyODhdDp58sknKSgowG63M2nSJPLz85k0aRJ2u52CggKefPJJnE5ntIcqIbQ0mYyf+mtfQ/7iyAT2izN+6q9V4FgkhumzhYiIiMS0602+7fYlU8NNFLRLzrDO808O+MeVuGCYpj6Y9oeCggJz//790R6GiIj0o9raWpYtW8arr75KOP/eGobBvHnzWLduHdnZ2f0wQgmH6z036b9KxzDa3sO/rvNO4TW80w3A/H7nMYxv+La9PwtX6+DfR7S1GdQ/UE/G7faIjl0GD8MwqkzTLIj2OCQ26LOFiIiIeNU74cfjffsP7+ndTOiaSvhFsW//q+9rdsEg1Nnni0E7s0BERCSaysvLycvLo6KiIihR4HA4yMvLw+FwBLSbpsmWLVvIy8ujvLy8P4crN2BPq/YlCuyO4LU+e2pYlhUPMAwTe1p1ZOKKiIiIiEj8+MP/8W1HcsnUUPFl0FOyQEREJMLWr19PaWkpLpfL21ZSUsLWrVupq6vj9OnTHD58mNOnT1NXV8fWrVspKSnx9nW5XJSWlrJ+/foojF46SrxyyrdjS4tscJtvJkHiVSULRERERESkm45X+Lb7YMnUgPgy6ClZICIiEkHl5eUsW7bMuz9+/HgqKyvZvn07c+fOJTMz8Kn0zMxM5s6dy/bt29mzZw+5ub7pncuWLdMMg1jjaYhwPHdk44mIiIiISPxo8cDVC759x4zIxB3rF+fqBes6EheULBAREYmQ2tpalixZ4t0vLCykqqqKGTPC+x+2oqIiDhw4QGFhobdtyZIl1NbWRnys0g3+63O6a6DpkrXd2MP3pf28q3VWvHZp43oWT0RERERE4tOlE77tPloyNeg6MqgpWSAiIhIhy5cv9y49lJuby7Zt23juueew2+0YhtHll91u57nnnmPbtm3eGQYul4vly5dH8bsSMicCvkLG1OyFY+XwfF7P4j2fZ53/wV6/RqPtOiIiIiIiImG6dNy33YdLpipZED+ULBAREYkAp9NJRYVvLceysjIyMjJYtWoVjY2NYcVobGxk1apVZGRkUFZW5m2vqKjA6XRGfMwSpkQbpIz07f/nt+H1Umh29Sxes8s6/z+/7WtLGWldR0REREREJFxX/JYg6sslU6+ej2xsiVlKFoiIiETApk2bME0TsIoZFxUVAYSdKGjX3r+oqIjZs2cDYJommzZtitxgpftuvde3XXc0ZBfjG51/hVR3LHR8ERERERGRcKTc7Nv2XzK1tzoumZpyS2TiSsxTskBERCQCdu3a5d1evHhxRGL6x9m9e3dEYkoPJYWY0ju6kNTU1G6FSU1NhdGFwQdCxRcREREREbmRzEmB+zV7Q/frrg86xMnQkqnxQskCERGRXvJ4PBw6dMi7H25B4674xzl48CAejycicaUHPvxD4H56Ljy4jVWrVoWdMEhNTWXVqlXw4LbAoskAH+6PzDhFRERERCR+dKx7dnBjZOJ2jKP6anFDyQIREZFeqq6u9t7IdzgcZGZmAlBbW9ujeO3nZWVl4XA4ACshUV1dHYHRSre1eODCwcC22WWQnMGKFStwu92Yptnll9vtZsWKFZCcYZ3v78J/W9cREREREREJV6INkm/y7Z/aATWVvYtZUwmndvr2h92k+mpxRMkCERGRXmpqavJup6VZy8mUl5eTl5fXo3h5eXmUl5cDYLfbve3Nzc29GKX0WEM1tF7z7Y8rAUdR72I6imDcbN9+6zXrOiIiIiIiIt1x+/zA/Z0LocnVs1hNLut8f5Pmh+wqg5OSBSIiIr2UkOD757ShoYH169dTWlqKy+XqUTyXy0VpaSnr16/H7XZ72w3D6O1QpSeuNwXu50emJkVQnBYlg0REREREpJv+5O8D9+ud8Oqc7icMmlzWefXOG8eXQU3JAhERkV66ds331HlNTQ3Lli2LSNxly5ZRU1MT8jrSj4wO/7vkiExNCsZ2jKNkkIiIiIiIdFN6Loz/XGDb2X3w4vTwlySqqbT6n90X2D7+c8H11mRQU7JARESkl06dOhWyvbCwsEfxOjtPNQtigN0ByZmRiTUsy4onIiIiIiLSG7M2wZDhgW31TvhFMVSUwImtcLUu8PjVOqu9osTq13FGwZDhVlyJK0OiPQAREZGB7vz580Ftubm5bNu2zVvsuDu2bdvG9OnTcToD/2ft3LlzPR6j9ILZ6tu2pUU2ts3ut2NGNraIiIiIiMSH1GyY/Ry8Xhp87NROX8Fiu8P6DOJxg7smuK+/2c9ZcSWuaGaBiIhIL91yyy1BbWVlZWRkZJCamtqtWKmpqWRkZFBWVhZ0bOTIkT0eo/SC/zJEnobIxva4/Xa0DJGIiIiIiPTQ5AVQ/OyN+7hr4OK7XScKip+14kncUbJARESklyZOnBiwX1JSQlFREQCrVq0KO2GQmprKqlWrACgqKmL27NkBx2+77bZej1V6yV0DTZciE+tqXdf/ky4iIiIiIhKu6Uvhc6+ALb1n59vSrfOnL43suGTAULJARESklzomCxYvXuzdXrFiBW63G9M0u/xyu92sWLEiZJxQ15F+4r8MEUDN3sjE/aBjHC1DJCIiIiIivTR5ATz8a0gd073zUsdY52lGQVxTskBERCTCZsyYEVNxpJeGJAfuH9wYmbgd4yQmRSauiIiIiIjEr2PlsPmz0Hime+c1nrHOO1beN+OSAUEFjkVERHqpurrau+1wOHpU1DiUrKwsHA4HNTU13utodkEUpOVAwlBovWbtn9oBNZXgKOp5zJpKX5ExsOKn5fQ8noiIiIiIyIH1sGdZYNu4EshfDNmFVg22lmbrQSVbGtTusx5iOrXD6tvssookXzmvpYjilJIFIiIivdTU1OTdTktLi2hsu93u3W5ubo5obAlTog1uzodzVb62nQvhkQOQnNH9eE0u63x/N3/cuo6IiIiIiEhPHCsPTBSkj4fZZeDwm7E+fGTgORPnWl81ldZnlHqn1b5nGaTcoiWJ4pCWIRIRiTEej4cTJ05w6NAhTpw4gcfjifaQpAvJyb5lahoaGiIa2+12e7eTkrRMTdTkzArcr3fCq3OsG//d0eSyzmv/n3Bv/Jm9GZ2IiIiIiMSzxlrYvcS3P7oQHqkKTBTciKPIehhqdKGvbfcSK67EFSULRERigNPp5Mknn6SgoIDhw4czadIk8vPzmTRpEsOHD6egoIAnn3wSp9PZdTDpdzk5Odhs1lPhNTU1XLp0KSJx6+rqvEsQ2Ww2cnK0TE3U5C8CjMC2s/vgxenWUzjhqKm0+p/d1+GA0RZfRERERESkB/Yst5YQAkjPhQe3dX8WdHKGdV56rrXf7LLiSlxRskBEJIpqa2uZP38+48ePZ82aNVRVVXH9+vWAPtevX6eqqoo1a9Ywfvx4HnroIWprld2PJTabjWnTpnn39+7dG5G4/nHy8/O9CQmJgvRcmDQvuL3eCb8ohooSOLEVrtYFHr9aZ7VXlFj9Os4oACtu+/+Qi4iIiIiIdEe9E45X+PZnl/VsuVSwzptd5ts/XhH6M4wMWkoWiIhESXl5ObfffjsVFRVdd/azZcsWbr/9dsrLy/toZNITs2b5lqnZuHFjRGL6x5k5U8vURF3xOkjK8O0bib7tUzvhtQfh30fAplvh+Tzr9d9HWO3+xYz9z0vKsOKKiIiIiIj0xMFNgGltjyuxlhTqDUcRjJvdtmO2xZd4oWSBiEgUrF+/ntLSUhobG0Medzgc5OXl4XA4Qh5vbGyktLSU9evX9+UwpRsWLVqEYVjL1OzYsYPKyspexausrGTnTusGs2EYLFqkZWqiLjUbZm7w7ZstMCSFoOWJ3DVw8V3rNYBh9TdbfE0zN1hxRUREREREeqJ6l287f3FkYvrHqd4dmZgyIChZICLSz8rLy1m2bFlQe0lJCVu3bqWuro7Tp09z+PBhTp8+TV1dHVu3bqWkpCTonGXLlmmGQYzIzc1l3jzfMjULFy7E5XL1KJbL5WLhwoXe/Xnz5pGbq2VqYsLkBVD8rG//+hXAtJYRypgACR2WikqwWe3puVa/61d8x4qfteKJiIiIiIj0RIsHLhzy7Ydb0LgrY/3iXDhoXUfigpIFIiL9qLa2lkcffTSgbfz48VRWVrJ9+3bmzp1LZmZmwPHMzEzmzp3L9u3b2bNnT9BN40cffVQ1DGLEunXryMjIAKyi1XPmzOl2wsDlcjFnzhxvMeuMjAzWrdMyNTFl+lL43CuBSxLVO8F1Elo9MHwUpI+3Xls9Vrv/Op9JGdb505f298hFRERERGQwaai2PnMA2B2QnHnj/uEalmXFAyt+Q3Vk4krMU7JARKQfPfroo3g8vox8YWEhVVVVzJgRXva/qKiIAwcOUFhY6G3zeDxBCQiJjuzsbDZs8C1Ts2/fPqZPnx72kkSVlZVMnz6dffv2eds2bNhAdraWqYk5kxfA40dg0nyCliG6/CHUv2+9BjCs/o8f0YwCERERERHpvetNvm1bWmRj2+y+7ZbmyMaWmKVkgYhIP3E6nbz55pve/dzcXLZt2+Z9Ej1cGRkZbNu2LWCGwZtvvul9El2ia8GCBTz7rG+ZGqfTSXFxccAyU/78l5kqLi4OeB+fffZZFizQTeWYlZoND2yGr56EO1fCyAJI7LAMUaLNar9zpdXvgc2qUSAiIiIiIpFh+N3a9TRENrbH7X+hyMaWmDUk2gMQEYkX//AP/xCwX1ZW1u1EQbuMjAzKysooLi4OiP/SSy/1ZogSIUuXLuWWW25hyZIl3mWIdu7c6S1Y7HA4sNvtuN1uamo6FsG13t8NGzYoUTBQpOfC3autr5a2KbotzZCYBGk5wQkEERERERGRSHPXQNOlyCxFdLXOiidxRzMLRET6yf/7f//Pu11SUkJRUVGv4hUVFTF79uyQ8SX6FixYwJEjR5g/fz6GEfgURk1NDe+++25QosAwDObPn8+RI0eUKBioEm2QORFummq9KlEgIiIiIiJ9xWwN3K/ZG5m4H3SMY0YmrsQ8JQtERPqBx+Ph8uXL3v3FixdHJK5/nMuXLwfUQ5Doy87OZvPmzZw8eZKVK1dSUFCAzRZ489hms1FQUMDKlSs5efIkmzdvVo0CERERERER6dqQ5MD9gxsjE7djnMSkyMSVmKdliERE+sG7774bsB9uQeOudIzz7rvv8olPfCIisSVycnNzWb16NatXr8bj8VBdXU1zczNJSUnk5OQEJRBEREREREREupSWAwlDofWatX9qB9RUgqOo5zFrKuHUTt9+wlDrOhIXNLNARKQf/P73v/duOxwOMjN9awiuXbsWu92OYRhdftntdtauXes9NysrC4fDEfI6EptsNhsTJ05k6tSpTJw4UYkCERERERER6ZlEG9ycH9i2cyE0uXoWr8llne/v5o9redU4omSBiEg/8F8eKC0tLeDYqlWraGxsDCtOY2Mjq1atCmiz2+3e7WvXrvV8kCIiIiIiIiIysOTMCtyvd8Krc7qfMGhyWefVOzvEn9mb0ckAo2SBiEg/GD9+vHe7oaEh4Fi4iYLO+rvdbu92bm5uD0YnIiIiIiIiIgNS/iLACGw7uw9enG4tKRSOmkqr/9l9HQ4YbfElXihZICLSDz71qU95t2tqarh06VJE4tbV1VFTUxPyOiIiIiIiIiIyyKXnwqR5we31TvhFMVSUwImtcLUu8PjVOqu9osTq13FGAVhx0/VQYjxRgWMRkX5w8eLFgP29e/cyd+7cXsfdu3dv0HWysrJ6HVdEREREREREBojidVC9G5pd1r6RCGaLtX1qp69gsd0BNjt43OCuCY7jf15ShhVX4opmFoiI9IOmpqaA/Y0bN0Ykbsc4zc3NEYkrfafF04rrRDMXDzXhOtFMi6c12kMSERERERGRgSw1G2Zu8O2bLTAkhaDlidw1cPHdEIkCw+rfnigAK15qdl+NWGKUZhaIiPSD5OTkgP0dO3ZQWVlJUVFRj2NWVlayc+fOgLakpKQex5O+0+D0cGRTHTW7Grl4qJlWj+k9lmAzGDEtCcesVPIWZZGWa4viSEVERERERGRAmrwArpyHPcus/etXrNf0XDASoKEGWj2+/gk2SHOA2WotQdTeH6D4WSuexB0lC0RE+kFOTg42mw2Px/cP88KFCzlw4ECP4rlcLhYuXBjQZrPZyMnJ6dU4JbIu117jrWVnOflqA5ih+7R6TC5UNXGhqokDz3zEhHlp3L1uNMOzh/bvYEVERERERGRgm74UUm6B3Ut8SxL51yIYPsqaQXD9Clz+EFwnA89PyrBmFChRELe0DJGISD+w2WxMmzYtoM3pdDJnzpwexZszZw5OZ2Dxofz8fGw2PZUeK06U1/PzvBOcrAhOFKQ6hpKVl0Sqo0NCwISTWxr4ed4JTpTX999gRUREREREZHCYvAAePwKT5hO0DNHlD6H+fes1gGH1f/yIEgVxTjMLRET6yaxZs6iqqgpo27dvX49ihTpv5syZPYolkXdw/UXeWnY2oO3WklTyFmeRPWM4yZmJ3vamSy3U7r3MkY11nN7RCECzq5U3Smu4ev46+UtH9OvYRUREREREZIBLzYYHNluzCg5usooff3QQWvyWIUq0wU35kDMT8hdZyxVJ3DNMs5N1ESSiCgoKzP3790d7GCISRU6nkwkTJtAXf3cNw+DkyZPk5uof92g7UV7PG6W+YlFp44dyb9lYxswY3uW5Zyob+fXCMzQ4r3nb7nvFwcQF6X0yVhEZOAzDqDJNsyDa45DYoM8WIiIi0m0tHmiohpZmSEyCtBwrYSBxqbPPF1qGSESkn+Tm5jJv3jzv/s0330x6es9uAqenp3PzzTd79+fNm6dEQQy4XHuNvUvOePdHFQ7j4arbwkoUAIwpSuXhA7cxqnCYt23vkjNcrr12g7NEREREREREupBog8yJcNNU61WJAglByQIRkX60bt06hg+3bhxfuHCB2267jby8vG7FyMvL47bbbuPChQsADB8+nHXr1kV8rNJ9by0/S7OrFYC03KF8fts4kjISuzgrUFJGIp/fNo60XKueQbOrlbeWn+3iLBERERERERGR3lGyQESkn/kvQ1RVVcWVK1d4+eWXWblyJQUFBUFFim02GwUFBaxcuZKXX36ZK1euBNQ+0HJysaHB6bGKGbe5t2xMyERBi6cV14lmLh5qwnWimRZPa1CfpIxE7i0b490/WdFAg9MT1E9EREREREREJFJU4FhkAPJ4PFRXV9PU1ERycjI5OTlBN5glNi1fvpwrV64EtDmdTv78z/+c2bNn8+1vf5vCwkLcbjfNzc0kJSVht9vZt28fGzduZM2aNUExr1y5wvLly9m8eXN/fRsSwpFNddCWt7m1JJUxRaneYw1OD0c21VGzq5GLh5pp9fgSPAk2gxHTknDMSiVvURZpudbv8piiVG6dncrpnY1gWvELV4/q1+9JREREREREROKHkgUiA4TT6WTTpk3s2rWLQ4cO4fH4njK22WxMmzaNWbNmsWjRIq1dH6OcTicVFRXe/f/1v/4X69evx+VyAbBz50527twJgMPhwG6343a7qampCYqVkZHB0qVLefrppwGoqKjA6XTqvY+iml2N3u28xVmAVcPg6yVP8cKhf6WZK6FP9ABV1lfSmhT+Iv9v+cH2f2J49lDyFmdZyQLgg92XYXUffxMiIiIiIiIiEre0DJFIjKutrWX+/PlMmDCBNWvWUFVVFZAoAGumQVVVFWvWrGHChAk89NBD1NbWRmnE0plNmzZ5lwwqKSnhu9/9LkeOHGH+/PkYhhHQt6amhnfffTcoUWAYBvPnz+fIkSN897vfZfbs2YC1FNGmTZv65xuRIC2eVi4eavbuZ88Yzonyen6ed+LGiYIOmrnCCwf/lZ/nneBEeT3ZM1K8xz462BRyySIRERERERERkUhQskAkhpWXl5OXl0dFRUXQuvQOh4O8vDwcDkdAu2mabNmyhby8PMrLy/tzuNKFXbt2ebcXL14MQHZ2Nps3b+bkyZNh1Sw4efIkmzdvJjs7OyAOwO7du/vhu5BQ3NXXvEsLpTqGcvxFF2+U1tDsag07UdCumSs0u1p5o7SG4y/Vk+qwCh23ekzc1dciPnYREREREREREdAyRCIxa/369SxbtiygraSkhMWLFzNjxgwyMzO97ZcuXWLv3r1s3LiRHTt2AOByuSgtLeX8+fMsXbq0X8cuwTweD4cOHfLuz5gxI+B4bm4uq1evZvXq1d6aFO01C25Uk8I/zsGDB/F4PKpfEQUtTb5knmmavLXsbMh+/5dDIdsB/oZpQW1vLTvL8DG+f6pbmlXMWkRERERERET6hmYWiMSg8vLygETB+PHjqaysZPv27cydO5fhw4dz4sQJDh06xIkTJxg+fDhz585l+/bt7NmzJ2Dd+mXLlmmGQQyorq72Lh/lcDgCkj0d2Ww2Jk6cyNSpU5k4ceINb/5nZWV5Z5e0Jxmk/yUm+5aRunzmund7VOGwHsXzP+9yrS9eYpIRqruIiIiIiIiISK8pWSASY2pra1myZIl3v7CwkKqqKm699VaefPJJCgoKsNvtTJo0ifz8fCZNmoTdbqegoIAnn3ySnJwcDhw4QGFhoTfGkiVLVMMgypqamrzbaWlpEY1tt9u9283NzTfoKX3FnjOUBFvbjfy2h//Tcofy+W3jehTv89vGkZY7NCBegs3AnjO0dwMVEREREREREemEkgUiMWb58uW4XC7AWprmueee46tf/Wq3Chx/7Wtf47nnnvPOMHC5XCxfvry/vxXxk5yc7N1uaGiIaGy32+3dTkpKimhsCU+iLYGMSYE38u8tG0NSRmKP4iVlJHJv2ZiAtszbbSTa9M+2iIiIiIiIiPQN3XUQiSFOp5OKigrv/iOPPMKnP/3pkAWOO9Ne4PjTn/40jzzyiLe9oqICp9MZ8TFLePzrDtTU1HDp0qWIxK2rq6Ompgawli/KycmJSFzpvqGpvsTArSWpjClK7VW8MUWp3DrbF2PIcP2TLSIiIiIiIiJ9R3ceRGLIpk2bvEmBKVOm8PTTT3tnGXSXy+Xi6aefZvLkyYCVRNi0aVOkhirdZLPZmDbNV8B27969EYnrHyc/P1/FjaPoWmOrdztvcRYAl2uv9ShW+3ntcQCuX27trLuIiIiIiIiISK8pWSASQ3bt2uXdPnr0aERiHjt2zLu9e/fuiMSUnpk1a5Z3e+PGjRGJ6R9n5syZEYkp3dfiacV13Lc8WPaM4Zwor+fneSd6FO/neSc4UV5P9owUb9ul9zy0eJQwEBEREREREZG+oWTBIOXxeDhx4gSHDh3ixIkTQWvcS+zxeDwcOnQoqN2/UHF3hDrv4MGD+lmIokWLFmEYVhHcHTt2UFlZ2at4lZWV7Ny5EwDDMFi0aFFvhyg95K6+RqvHmhWU6hjK8RddvFFaQ7Mr8Ob+3zCt0y9/za5W3iit4fhL9aQ6rFoIrR4Td3XPZiqIiIiIiIiIiHRFyYJBxOl08uSTT1JQUIDdbmfSpEnk5+czadIk7HY7BQUFPPnkk1q3PkZVV1cH3cjPzc1l27ZtPYq3bds2b4Hjdh6Ph+rq6h6PUXonNzeXefPmefcXLlzYq2WmFi5c6N2fN29e0Pst/aelyVdTxDRN3lp21rufbKSEOqVT/v3fWnYWs9UXu6U5vNolIiIiIiIiIiLdpWTBIFBbW8v8+fOZMGECa9asoaqqKuims8fjoaqqijVr1jBhwgQeeughamtrozRiCaWpqSmoraysjIyMjB7Fy8jIoKysLKi9ubm5R/EkMtatW+d9T51OJ3PmzOl2wsDlcjFnzhxv4i8jI4N169ZFeKTSHYnJhnf78pnr3u2bP5nMn0/5W5IIL2GQRApf/tjfcvMnk33xan3xEpOMUKeJiIiIiIiIiPTakGgPQHqnvLycJUuWhLzZ6HA4SEtLo6GhgZqaGm+7aZps2bKF3bt3s2HDBhYsWNCPI5bOJCcnB+yXlJRQVFTUq5hFRUXMnj3bu1QNQFJSUq9iSu9kZ2ezYcMGSktLAdi3bx/Tp0+nrKwsrPe7srKShQsXBswQ2rBhA9nZ2X01ZAmDPWcoCTbDWoqo7eH/YTcnUv8/HqbXlzKd0oD+qY6h2NIS8DS00ljTYWmhI1Cf7mHYzYlcvdDijZdgM7DnDO2H70ZERERERERE4pFmFgxg69evp7S0NCBRUFJSwtatW6mrq+P06dMcPnyY06dPU1dXx9atWykpKfH2dblclJaWsn79+iiMXjrKycnxrmcPsHjx4ojE9Y9jGAY5OTkRiSs9t2DBAp599lnvvtPppLi4OOD315//729xcXFAouDZZ59Vwi8GJNoSyJgUeCP/6oUWPPW+mgW3lqRy/9ZbeaJuCo+dvp0vHZ7IY6dv54m6Kdy/9VZuLUn19vXUt1qJAj+Zt9tItOmfbRERERERERHpG4Zpav3j/lBQUGDu378/YvHKy8u9TyYDjB8/nrKyMmbMmAH41qZvamoiOTmZnJwcbDYbEPrJ5FdeeUU3HKPM4/GQnJxM++9kXV0dmZmZAAFJhHD5xxkxYoQ3TlNTk/dnQaKrq5lBdrsdt9sdMDOoXUZGhmYGxZgthSc597urQe1p44dyb9lYxswY3mWMM5WN/HrhGRqcwYWMR35qGPP3TYjIWEVk4DEMo8o0zYJoj0NiQ6Q/W4iIiIhIfOns84UeURyAamtrWbJkiXe/sLCQqqoqbr311rAKHOfk5HDgwAEKCwu9MZYsWaIaBlFWXV3tvcHvcDi8iYLeysrKwuFwAFYCQQWOY8eCBQs4cuQI8+fPD0oI1dTU8O677wYlCgzDYP78+Rw5ckSJghhzrbE1qG1U4TAerrotrEQBwJiiVB4+cBujCocFHbt+OTi+iIiIiIiIiEikKFkwAC1fvtz7JHJubi7PPfccX/3qV7tV4PhrX/sazz33HLm5uYC1JNHy5cv7+1sRP/4FjtPS0iIa2263e7dV4Di2ZGdns3nzZk6ePMnKlSspKCgImvlhs9koKChg5cqVnDx5ks2bN6tGQYxp8bTiOh74dzctdyif3zaOpIzEbsVKykjk89vGkZYbuKzRpfc8tHiUMBARERERERGRvqECxwOM0+mkoqLCu//II4/w6U9/uscFjpcuXcrTTz8NQEVFBU6n05tAkP7lX+C4oaEh4FhqaiqNjY1hx0pNTQ3Yd7vd3m0VOI5Nubm5rF69mtWrV3uXEWtubiYpKSlgGTGJTe7qa1ZxYz/3lo3pdqKgXVJGIveWjeGXxae8ba0eE3f1NTIm6ndYRERERERERCJPMwsGmE2bNnmXqpkyZQpPP/10rwocP/3000yePBmwkgibNm3q1+9HfEaPHu3drqmp4dKlS979VatWBSUAOpOamsqqVau8+3V1dQHJIv/rSGyy2WxMnDiRqVOnMnHiRCUKBoCWpsBEwa0lqYwpCu93tjNjilK5dXZgjJZm1RkSERERERERkb6hZMEAs2vXLu/20aNHvdvjx4+nsrKS7du3M3fu3KD17jMzM5k7dy7bt29nz549AbMHjh075t3evXt3H45ebuTs2bMB+3v37vVur1ixArfbjWmaXX653W5WrFgRMk6o64hI7yUmB9acyFucFZG4HeMkJnW/2LmIiIiIiIiISDiULBhAPB4Phw4dCmpvL3A8Y8aMsOIUFRUFFThud/DgwaB6B9I//GsWAGzcuDEicTvGUc0CkchLGR24ql92mAWNu5I9I+WG1xERERERERERiRQlCwaQ6urqoBv5ubm5bNu2jYyMjIB2j8fDiRMnOHToECdOnAg6LyMjg23btgXVJ2hfK136X0tLS8D+jh07qKys7FXMyspKdu7cGdB2/fr1XsUUkWBXzvp+r1IdQ0nO7Fmtgo6Ss4aQ6vAVOva/joiIiIiIiIhIJClZMIB0fPIcoKyszJsocDqdPPnkkxQUFGC325k0aRL5+flMmjQJu91OQUEBTz75JE6nE7ASBmVlZUEx9eR5dNTW1ga1LVy4MGTx6nC4XC4WLlwY1nVEpHf8axbY0iL7T+tQuy+eahaIiIiIiIiISF9RsmAASU5ODtgvKSmhqKiI2tpa5s+fz4QJE1izZg1VVVVBMwk8Hg9VVVWsWbOGCRMm8NBDD1FbW0tRURGzZ88O6JuUlNTn34sEu3r1qnc7IcH61XQ6ncyZM6fbCQOXy8WcOXO8iaH2eKBkkEhf8K9Z4GlojWjsa25fPNUsEBEREREREZG+omTBAJKTk4Nh+G4ULV68mPLycvLy8qioqMA0w3vi1DRNtmzZQl5eHuXl5SxevNh7zDAMcnJyIj526VpaWpp3279A9b59+5g+fXrYSxJVVlYyffp09u3bFzJeampq7wcrIgHsOUNJsFl/nxtrrtF0ybes2Nq1a7Hb7RiG0eWX3W5n7dq13nOb6q7TWHMNgASbgT1nKCIiIiIiIiIifUHJggHsvffeo7S0tFfL1JSWlvLee+9FdmDSI/4Fpy9evMiaNWu8+06nk+LiYkpKSti6dSt1dXUB59bV1bF161ZKSkooLi72zigAWL16NRcvXgx5HRGJjERbAhmTbN792r2XvdurVq2isbExrDiNjY2sWrXKL84V73bm7TYSbfpnW0RERERERET6xpBoD0DCV11d7Z09MGLECFauXBmRuE8++SQjRozg4sWLmKZJdXU1EydOjEhsCV9qaiopKSlcuWLdHLz99tt55ZVXWLJkiTchtHPnTm/BYofDgd1ux+12U1NTExQvIyODDRs2YLP5bmCmpKRoZoFIHxma6ruRf2RjHePnWrOFwk0UtPPvf2SjLzE4ZLgSBSIiIiIiIiKDQosHGqrhehMMSYa0HEi0dX1eH1OyYADxL3B86dIl73ZhYWHAkjPh8j/PP57WtI+e/Px8fve73wGwceNGtm/fzt13383y5cuDlpoKlSAAaympefPmsW7dOrKzsykpKQmILyJ941qjb+mh0zsaOVPZyJiiwOSc+f3Ozze+Ebh/prKR0zt9iYPrlyNbC0FERERERERE+lG9Ew5ugupdcOEgtF7zHUsYCjfnQ84syF8E6blRGaIeUxxA/IvUtrZaN41yc3PZtm1bj+Jt27aN3NzcgHhAQF0E6V/PPPOMd3vHjh1UVlaSnZ3N5s2bOXnyJCtXrqSgoCBgtgCAzWajoKCAlStXcvLkSTZv3kx2djaVlZXemQgd44tI5LR4WnEdvxbQ9uuFZ2h2tXRyxo01u1r49cIzAW2X3vPQ4lHCQERERERERGRAaayF1+bDj8fD79fAuarARAFY++eqrOM/Hg+/esg6r59pZsEAV1ZWRkZGRo/OzcjIoKysjOLi4sgOSnrsnnvuYcyYMZw5Y90kXLhwIQcOHCAjI4Pc3FxWr17N6tWr8Xg8VFdX09zcTFJSEjk5OUEJBJfLxcKFC737Y8aM4Z577unX70ckXrirr9HqaZv5YwAmNDiv8R9zTvUo3n/MOUWD81pAvFaPibv6GhkTkyIxZBERERERERHpa8fKYdci8DR077zjW+DUGzBrE0xe0DdjC0EzCwYQ/6f/AUpKSigqKupVzKKiImbPnh3Q5r/UjfS/1157zTu7w+l0MmfOnKAi1jabjYkTJzJ16lQmTpwYMlEwZ84cb6FjwzB47bXX+mX8IvGopcn3d3P4GF8e/sN9V3sUz/+84dm+eC3N+vssIiIiIiIiMiAcWA+vl3aeKLA7YESe9RqKp8E6/8D6vhtjB0oWDCDJyckB+4sXL45I3I5xkpL01Go0TZ8+naVLl3r39+3bx/Tp06msrAzr/MrKSqZPnx5Qx2Lp0qVMnz490kMVkTaJyb7l2wzD4O5nR0ck7t3PjsZI8MVOTNIycSIiIiIiIiIx71g57FkW3D6uBL6wFf66DhadhscPW69/XWe1jysJPmfPMiteP1CyYAAZPTrw5tOMGTMiErdjnI7Xkf63bt065s2b5913Op0UFxdTUlLC1q1bqaurC+hfV1fH1q1bKSkpobi42DujAPAWOxaRvmPPGUqCzbqR31hzjUmPZHDfKw4yx37Uo3iZYz/ivlccTPpyOo011nJECTYDe87QiI1ZRERERERERPpAYy3sXBjYlj4eHq6Eedth4lxIzgw8npxptc/bDg/vCS5wvHNhv9QwULJgADl79qx32+FwkJmZeYPe4cvKysLh8E138b+ORM+WLVtYtmxZQMHpnTt38uCDDzJixAhuvfVW8vLyuPXWWxkxYgQPPvhgQDFjwzBYtmwZW7ZsicbwReJKoi2BEdN8s7Jq915m4sd38KVvfrFH8b70zS8y8eM7qN17xdt2U34yiTb9sy0iIiIiIiIS03Ytguu+z/OMLoRHqsAR5oPfjiJ45IB1XrvrV6y4fUwFjgeQpqYm73ZaWlpEY9vtdu92c3NzRGNLz61bt47HHnuML3zhC96ix+1qamo6PW/MmDG89tprWnpogLpadx3naw146lqwZSWS+4U0hmXpz3Wsc8xK5UKV9Xf68rZ/gZNP0XHRIOMb4cUyrrng9VIuH/snYD4AY2cOj9hYRURERERERKQP1Dvh/dd9++m58OA2SM7oXpzkDOu8F6dbMcGKW+8MnnUQQXpEcQDxr1nQ0NDNCtpdcLvd3m3VLIgt06dP54MPPmDv3r186lOfIiUlJWS/lJQUPvWpT7F3714++OADJQoGmOPlLn4y5hj/lniYshHH2POVWt5ecY49X6mlbITV/pMxxzhe7or2UKUTeYuywIDbPr6Dabc/5W1P7WadAf/+0yY/xW0f3wFGW3wRERERERERiV1/+D+B+7PLup8oaJecYZ1/o/gRpmTBAJKTk0NiYiJgPVV+6dIl77HPf/7z3Yrl37+urs77lHpiYiI5OTkRGK1E2j333MO+ffu4fPkybrebN954g1dffZU33ngDt9vN5cuX2bdvH/fcc0+0hyrdcHqnmw3DjrCr9AOu1F6H1k46tsKV2uvsKv2ADcOOcHqnu5OOEi1puTY+VnqVGfO+62scXciqVd8lNTU1rBipqamsWvXdgKmGM+Z9l4+VXiUt1xbpIYuIiIiIiIhIJJ34pW97XIm1pFBvOIpg3OzQ8fuA1rUYQGw2G0lJSVy5Yq15tXfvXubOnQvAr371qx7H3bt3r3c7KSkJm003pGJdamoqs2bNivYwpJd+df8pTu9oDHks1TEUW1oCnoZWb4Hbdi1NJr8qqebWklQe2D6uH0Yq4bp77hqG1LQlctqmGq5IzmDFyn/oXqCmv/FONUxOcXP33DVARcTHKyIiIiIiIiIR0uKBK+d8+/mLIxM3fzGcaqtTeuWcdZ3Evrl/q5kFA4jH4wmoW7Bx48aIxPWP09TUhMfjiUhcEencK5/4n6BEwa0lqdy/9VaeqJvCY6dv50uHJ/LY6dt5om4K92+9lVtLAp9OP72jkVc+8T/9OWy5kXonQ2q2+vYjONVwSM1W3xqFIiIiIiIiIhJ7Lp0ATN9+uAWNuzLWP47Zdp2+oWTBAFJdXU1rq2+Nkh07dlBZWdmrmJWVlezcudO739raSnV1da9iisiN/er+U1z8b7+C5eOH8v+3d+9xUlR3/v/fh2EuwNy4qAEchgFBE3SSsKwJyRLAYCAkZlkxYr4/szHoor/Nqps1+4373dtkv4/9YvYbs8Fk8xO+CXGz+f02imhuohgiQ0xC1hU2GYMxEJ0Zh4tRGIaZQebCcH5/nO6p7p7ume6ZqulLvZ6PRz+6qrrOp850ddd01afOOesa63Tdk3M1b12lyqYWxa1fNrVI89ZV6ron52rd3rmqrCsefO3UL3v0/Q+2jFfVMZymbRr8UeB7U0MbiQ8AAAAAAHJS7E1+FTVS2VR/4k6a5uJFdbb4EzcJkgV5JLZVQdTGjRvV0dExqngdHR3auHHjkOW9vb2jigdgZK/u7oprUfCWpZN044HLNHv5lLTKz15RrhsPXqa3LJ3kxXyqmzEMckHrD71pP5saDsbf409MAAAAAAAQrJJKn+NV+BsvBZIFeaSsrGxw2hgjSWpubtbatWszThh0dHRo7dq1am5ujosnuXELAARj17pXB6cr64r14V1zVVpdNEyJoUqri/ThXfEtDGLjIgsG+qSTL3jzQTQ1PNnktgMAAAAAAHJPVZ033dfpb+y+mJtEK+f6GzsGyYI8UltbOzj4sLVe/1f79+/X4sWL0+6SqLGxUYsXL9b+/fsHl0XjlZSUqLa21r9KAxh0+OEODfR4391rts9WaXWR7r//flVUVMgYM+KjoqJC999/v0qri3TN9tmDsQZ6rA4/3JGFvwqSpM5W70J+UE0NB/rcdgAAAAAAQO6ZusCb7mqTek77E/dcu4uXbDs+I1mQR0pKSnTVVVcNzt92222D083NzVq5cqXWrFmjxx9/XO3t7XFl29vb9fjjj2vNmjVauXLlYIsCSbr11lsHp+vr6wcTEgD89dO/eG1wes6acs1e4QYsbmhoUHd3d6picbq7u9XQ0CDJdUk0Z7U36HFsfIyz8zHdxI3U1HCgzw1G9MYL7nmk1gKxTQ0H6CYOAAAAAICcVFQiTZjozbft8yfu0Zg4Eya67QRk4sirIJdce+21OnDggCTp6NGj+va3v6077rhjsBui3bt3Dw5YXFNTo4qKCnV1damtrW1IrOrqaj344IP6xje+Mbhs1apVwf8RQEi9+dr5welFt08bnE43UZBs/UW3T9Oru7uHxMc4m+h1E5e0qeGZZjdAcesPXXdFsQmCohJpxlVS7bVS/ab4ZotSfFPDIrqJAwAAAAAgJw30SRcuePNNW6UF68Yet2mrN33hgttOQAkDWhbkmU2bNg2OL/DUU0/pkksu0aFDh3TDDTfEjTsgSW1tbXrxxReHJAqMMbrhhht06NAhXXLJJYPJBWOMNm3aND5/CBAy59rPSzH/L2alGND4K3oh5SOZWcsnezMXItvB+KuslRQ5Bsc2New+Ln3vBulr86Xn7pN+d2BoS4KBPrf8ufvcet//qCsnJTQ1NJHtAAAAAACAnNPZqriLPy1PSW2NyddNt9eBtkapZXfMgguBdlFMy4I8U1dXp/Xr1+vRRx+VJG3cuFEHDx7Ujh071NzcrG3btmnPnj1qampSX5/3ISspKVF9fb1WrVqlTZs2qa6uTh0dHdq4cePgOuvXr1ddXd2QbQIYu+bveXebl9cUq2xqZoMap1I2baLKa4rV3dY/uJ233TJthFIIXNs+12XQnjuk3o6hr1fUuO6K+jrj+x2UlQ4/KrXukVY9GGjTQgAAAAAA4KPYLoqjdm+Ubj4olVVn3utAT4crnyjALopJFuShLVu2aM+ePero6FBzc7PWrl2rXbt2qa6uTps3b9bmzZvV19en1tZW9fb2qrS0NG5wZEnq6OjQ2rVrB8cuqK6u1pYtW7L1JwEFr699YHC6pNLfRl3FFV68vo6BYdZEYDpbJXmDV+sn/0Nq/3X8OnPXSPW3SzXL4wdA7jntkgtNW91dB5JLMDxxkzTtipgA1m0nwIGMAAAAAADAKMV2USwjyboEwY5VUsVs6eXvK+7aQaxorwO/OyA993lp/kekrqOufGw8KdAuiumGKA/NmjVLDz744OD8/v37tXjxYjU2Ng4uKykp0YIFC3TllVdqwYIFcYmCxsZGLV68WPv37x9c9uCDD2rWrFnjUn8gjEqmeS0J+jovDLNm5vq7vHgl1f60WECGEu8eiE0UVM2TbmyU1j/p+iqMTRRIbn7BOvf6jXvjxyxofyl+XQY4BgAAAAAgN1XWSiZ6XSYmKfD6Aenl72lIoqCiRpq+yD3HsdLL33XlYpdJLn6AXRQXdLLAGHOpMWa7Mea4MabXGNNijPmSMWbqyKWHxFpmjNlpjDkRiXXCGPO0MWZtEHUfyYYNG/TAAw8Mzjc3N2vlypVas2aNHn/8cbW3t8et397erscff1xr1qzRypUrB1sUSNIDDzygDRs2jFvdgTCq+0jl4HR3W796TvvTAqCn/fxgF0SJ28E4irt7IMbMpdLNB1xrgnTUrHDNE2cuTf46AxwDQNYU8rkFAAAAfFBUEn/enuzcfu4a6SOPS59qlza9Kt3yK/f8qXa3fO6aoWVmvjtmG6WBdllcsN0QGWPmS/qZpIslfVfSS5KulnS3pDXGmPdaa0+lGetvJP1PSScl/UDSCUkzJL1T0gpJu/yufzruvPNOXXzxxbrjjjvU0dEhSdq9e/fggMU1NTWqqKhQV1fXkEGOJdf10IMPPkiiABgHk6ZNjGsxdnzfWc1bN/YL+8f3venNmMh2MP6mzBy6rKpOun6X65cwE2XVrty3Fsc0NxxmOwCAwIXh3AIAAABjNNAnDcT0PHDC69VFVfOk1dtT30wY7XVgwTo3qPHujd41gRM/j9lGj9tOQAmDQr6q9FW5H/N3WWu/HF1ojPmipE9L+kdJd4wUxBjzUbkf83skXW+t7Up4vdjPSmdqw4YNWrZsme6++27t3LlT1nrNWZIlCCTJGKP169dry5YtdD0EjKOJU4zOd7vv6KGt7b4kCw5t9VoRTZxixhwPo3T2xNBlq7dnniiIKqt25R9ZOXQ7JYxZAABZEIpzCwAAAIxBZ6tkk3Q9PXNpZjcTRnsdeGxtfMJBcvEDHM+wIJMFxph5kj4gqUXSvyS8/PeSNkn6uDHmHmvt2WHiTJD0eUlvSvpviT/mJcla2z+k4DibNWuWduzYoebmZm3btk179uxRU1OT+vq8EbVLSkpUX1+vVatWadOmTaqrqxsmIoAgTLpoorq63SHj1ae6dayxW7NXlMet82e6Ku14xxq79eru7rj4yJLEMQvmrnH/3MeiZoU0d7XUsttbxpgFADDuwnZuAQAAgFFKvDYgBdPrQIDXBgr1ytI1keenrY1P51hru4wxP5X7wf9uST8aJs57JNVJelTSaWPMhyRdKalH0nPW2v3DlB13dXV12rx5szZv3qy+vj61traqt7dXpaWlqq2tjRvkGMD4Gui7oLPHzscte2bjMd148DKVl5eru7s7RcmhysvL1dsxoGc2HotbfvbYeQ30XVBRSUEPR5ObTMJ7Xn+7P3Hrb49PFojWIwCQBaE8twAAAECGko1nGESvAwGOZ1ioV5QujzwfTvH6kcjzwhHi/H7k+XeSDsr1KXqfpC9J+pkxZp8x5qJUhY0xm4wxzxtjnn/jjTfSqrhfSkpKtGDBAl155ZVasGABiQIgy7pa+3WhL37U+87mfv1gbYv+5rN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      "text/plain": [
       "<Figure size 1872x2808 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(26, 39))\n",
    "\n",
    "marker_size = 500\n",
    "mean_field_marker_size = 100\n",
    "\n",
    "x_label_size = 40\n",
    "tick_size = 20\n",
    "legend_size = 25\n",
    "title_size = 35\n",
    "\n",
    "n_rows = 3\n",
    "n_cols = 2\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 1000000, 'WS3'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "beta = 0\n",
    "phi = 0\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.005, 0.01, 0.015, 0.02, 0.025]\n",
    "results = prepare_table_with_result_scenario_1(N, \n",
    "                                                m, x,\n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 1)\n",
    "sub.set_title('A', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "psi = 0\n",
    "color_ = 'k'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.04\n",
    "color_ = 'darkviolet'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.049\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "sub.set_xlabel(r'$\\alpha$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_1$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "sub.legend(fontsize=legend_size)\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "#\"\"\"\n",
    "\n",
    "N, T, topology_id = 2000, 1000000, 'complete'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "alpha = 0.025\n",
    "psi = 0.049\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.003, 0.006, 0.009, 0.012, 0.015, 0.018]\n",
    "results = prepare_table_with_result_scenario_2(N, \n",
    "                                                m, x, \n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 2)\n",
    "sub.set_title('B', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "phi = 0\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_2_public_op(N, \n",
    "                              results, \n",
    "                              table_mean_field_approx, \n",
    "                              sub, x, alpha, psi, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "\n",
    "sub.set_xlabel(r'$\\beta$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_{1}$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "#sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "#\"\"\"\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "geographic-license",
   "metadata": {},
   "source": [
    "# ... on complete graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "preceding-occasions",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1872x2808 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(26, 39))\n",
    "\n",
    "marker_size = 500\n",
    "mean_field_marker_size = 100\n",
    "\n",
    "x_label_size = 40\n",
    "tick_size = 20\n",
    "legend_size = 25\n",
    "title_size = 35\n",
    "\n",
    "n_rows = 3\n",
    "n_cols = 2\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 1000000, 'complete'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "beta = 0\n",
    "phi = 0\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.005, 0.01, 0.015, 0.02, 0.025]\n",
    "results = prepare_table_with_result_scenario_1(N, \n",
    "                                                m, x,\n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 1)\n",
    "sub.set_title('A', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "psi = 0\n",
    "color_ = 'k'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.04\n",
    "color_ = 'darkviolet'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.049\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_1_public_op(N, \n",
    "                               results, \n",
    "                               table_mean_field_approx, \n",
    "                               sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "sub.set_xlabel(r'$\\alpha$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_1$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "sub.legend(fontsize=legend_size)\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "#\"\"\"\n",
    "\n",
    "N, T, topology_id = 2000, 1000000, 'complete'\n",
    "t_freq = 500000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "alpha = 0.025\n",
    "psi = 0.049\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.003, 0.006, 0.009, 0.012, 0.015, 0.018]\n",
    "results = prepare_table_with_result_scenario_2(N, \n",
    "                                                m, x, \n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 2)\n",
    "sub.set_title('B', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "phi = 0\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_2_public_op(N, \n",
    "                              results, \n",
    "                              table_mean_field_approx, \n",
    "                              sub, x, alpha, psi, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "\n",
    "sub.set_xlabel(r'$\\beta$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_{1}$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "#sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "#\"\"\"\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cathedral-december",
   "metadata": {},
   "source": [
    "# ... in Scenario 3 (ranfdom geometric networks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "nuclear-document",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x936 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(13, 13))\n",
    "\n",
    "marker_size = 500\n",
    "mean_field_marker_size = 100\n",
    "\n",
    "x_label_size = 40\n",
    "tick_size = 20\n",
    "legend_size = 25\n",
    "title_size = 50\n",
    "\n",
    "n_rows = 1\n",
    "n_cols = 1\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 500000, 'random_geom'\n",
    "t_freq = 25000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [-0.02, -0.01, 0, 0.01, 0.02]\n",
    "results = prepare_table_with_result_scenario_3(N, \n",
    "                                               m, \n",
    "                                               x, \n",
    "                                               in_ops_type, \n",
    "                                               topology_id, selectivity_rate, pers_rate, th_value, t_freq, T, n_exp=20)\n",
    "\n",
    "sub = fig.add_subplot(n_rows, n_cols, 1)\n",
    "#sub.set_title('A', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "beta = -0.02\n",
    "color_ = 'k'\n",
    "plot_scenario_3_public_op(N, \n",
    "                          results, \n",
    "                          table_mean_field_approx, sub, x, beta, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "beta = 0\n",
    "color_ = 'darkviolet'\n",
    "plot_scenario_3_public_op(N, \n",
    "                          results, \n",
    "                          table_mean_field_approx, sub, x, beta, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "beta = -0.02\n",
    "color_ = 'darkorange'\n",
    "plot_scenario_3_public_op(N, \n",
    "                          results, \n",
    "                          table_mean_field_approx, sub, x, beta, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "sub.set_xlabel(r'$\\alpha$', fontsize=x_label_size)\n",
    "sub.set_ylabel(r'$y_1$', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "sub.legend(fontsize=legend_size)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "changing-people",
   "metadata": {},
   "source": [
    "# The effect of errors on assortativity (random geometric networks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "heated-fashion",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1872x1872 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(26, 26))\n",
    "\n",
    "marker_size = 500\n",
    "mean_field_marker_size = 100\n",
    "\n",
    "x_label_size = 40\n",
    "tick_size = 20\n",
    "legend_size = 25\n",
    "title_size = 50\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 500000, 'random_geom'\n",
    "t_freq = 25000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "beta = 0\n",
    "phi = 0\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.005, 0.01, 0.015, 0.02, 0.025]\n",
    "results = prepare_table_with_result_scenario_1(N, \n",
    "                                                m, x, \n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(2, 2, 1)\n",
    "sub.set_title('A, Scenario 1', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "psi = 0\n",
    "color_ = 'k'\n",
    "plot_scenaio_1_assrt(N, \n",
    "                                     results, \n",
    "                                     table_mean_field_approx, \n",
    "                                     sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.04\n",
    "color_ = 'darkviolet'\n",
    "plot_scenaio_1_assrt(N, \n",
    "                                     results, \n",
    "                                     table_mean_field_approx, \n",
    "                                     sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.049\n",
    "color_ = 'darkorange'\n",
    "plot_scenaio_1_assrt(N, \n",
    "                                     results, \n",
    "                                     table_mean_field_approx, \n",
    "                                     sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "sub.set_xlabel(r'$\\alpha$', fontsize=x_label_size)\n",
    "sub.set_ylabel('max assortativity', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "sub.legend(fontsize=legend_size)\n",
    "\n",
    "\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 500000, 'random_geom'\n",
    "t_freq = 25000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.003, 0.006, 0.009, 0.012, 0.015, 0.018]\n",
    "results = prepare_table_with_result_scenario_2(N, \n",
    "                                                m, x, \n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(2, 2, 2)\n",
    "sub.set_title('B, Scenario 2', fontsize=title_size, loc='left')\n",
    "\n",
    "phi = 0\n",
    "color_ = 'darkorange'\n",
    "plot_scenaio_2_assrt(N, \n",
    "                              results, \n",
    "                              table_mean_field_approx, \n",
    "                              sub, x, alpha, psi, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "\n",
    "sub.set_xlabel(r'$\\beta$', fontsize=x_label_size)\n",
    "sub.set_ylabel('max assortativity', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "#sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 500000, 'random_geom'\n",
    "t_freq = 25000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [-0.02, -0.01, 0, 0.01, 0.02]\n",
    "results = prepare_table_with_result_scenario_3(N, \n",
    "                                               m, \n",
    "                                               x, \n",
    "                                               in_ops_type, \n",
    "                                               topology_id, selectivity_rate, pers_rate, th_value, t_freq, T, \n",
    "                                               n_exp=20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(2, 2, (3, 4))\n",
    "sub.set_title('C, Scenario 3', fontsize=title_size, loc='left')\n",
    "\n",
    "beta = -0.02\n",
    "color_ = 'k'\n",
    "plot_scenaio_3_assrt(N, results, table_mean_field_approx, sub, x, beta, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "\n",
    "beta = 0\n",
    "color_ = 'darkviolet'\n",
    "plot_scenaio_3_assrt(N, results, table_mean_field_approx, sub, x, beta, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "beta = 0.02\n",
    "color_ = 'darkorange'\n",
    "plot_scenaio_3_assrt(N, results, table_mean_field_approx, sub, x, beta, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "sub.set_xlabel(r'$\\alpha$', fontsize=x_label_size)\n",
    "sub.set_ylabel('max assortativity', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "russian-province",
   "metadata": {},
   "source": [
    "# Erdős–Rényi networks (Scenario 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ranging-mercy",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 1872x936 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(26, 13))\n",
    "\n",
    "marker_size = 500\n",
    "mean_field_marker_size = 100\n",
    "\n",
    "x_label_size = 40\n",
    "tick_size = 20\n",
    "legend_size = 25\n",
    "title_size = 50\n",
    "\n",
    "\n",
    "\"\"\"\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 500000, 'random_geom'\n",
    "t_freq = 25000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "beta = 0\n",
    "phi = 0\n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.005, 0.01, 0.015, 0.02, 0.025]\n",
    "results = prepare_table_with_result_scenario_1(N, \n",
    "                                                m, x, \n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(2, 2, 1)\n",
    "sub.set_title('A', fontsize=title_size, loc='left')\n",
    "\n",
    "\n",
    "psi = 0\n",
    "color_ = 'k'\n",
    "plot_scenaio_1_assrt(N, \n",
    "                                     results, \n",
    "                                     table_mean_field_approx, \n",
    "                                     sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.04\n",
    "color_ = 'darkviolet'\n",
    "plot_scenaio_1_assrt(N, \n",
    "                                     results, \n",
    "                                     table_mean_field_approx, \n",
    "                                     sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "psi = 0.049\n",
    "color_ = 'darkorange'\n",
    "plot_scenaio_1_assrt(N, \n",
    "                                     results, \n",
    "                                     table_mean_field_approx, \n",
    "                                     sub, x, psi, beta, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "sub.set_xlabel(r'$\\alpha$', fontsize=x_label_size)\n",
    "sub.set_ylabel('max assortativity', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "sub.legend(fontsize=legend_size)\n",
    "\n",
    "\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "N, T, topology_id = 2000, 500000, 'random_geom'\n",
    "t_freq = 25000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [0, 0.003, 0.006, 0.009, 0.012, 0.015, 0.018]\n",
    "results = prepare_table_with_result_scenario_2(N, \n",
    "                                                m, x, \n",
    "                                                in_ops_type, \n",
    "                                                topology_id, \n",
    "                                                selectivity_rate, \n",
    "                                                pers_rate, th_value, t_freq, T, 20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(2, 2, 2)\n",
    "sub.set_title('B', fontsize=title_size, loc='left')\n",
    "\n",
    "phi = 0\n",
    "color_ = 'darkorange'\n",
    "plot_scenaio_2_assrt(N, \n",
    "                              results, \n",
    "                              table_mean_field_approx, \n",
    "                              sub, x, alpha, psi, phi, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "\n",
    "sub.set_xlabel(r'$\\beta$', fontsize=x_label_size)\n",
    "sub.set_ylabel('max assortativity', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "#sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "########################################################################################################################\n",
    "\"\"\"\n",
    "\n",
    "N, T, topology_id = 2000, 500000, 'Erdős–Rényi'\n",
    "t_freq = 25000\n",
    "m, possible_ops, th_value = 2, np.array([-1, 1]), 0\n",
    "selectivity_rate, pers_rate = -0.01, -0.01  \n",
    "in_ops_type = ('uniform', )\n",
    "main_folder = 'New_experiments_noise'\n",
    "x = [-0.02, -0.01, 0, 0.01, 0.02]\n",
    "results = prepare_table_with_result_scenario_3(N, \n",
    "                                               m, \n",
    "                                               x, \n",
    "                                               in_ops_type, \n",
    "                                               topology_id, selectivity_rate, pers_rate, th_value, t_freq, T, \n",
    "                                               n_exp=20)\n",
    "\n",
    "\n",
    "sub = fig.add_subplot(1, 2, (1, 2))\n",
    "#sub.set_title('C, Scenario 3', fontsize=title_size, loc='left')\n",
    "\n",
    "beta = -0.02\n",
    "color_ = 'k'\n",
    "plot_scenaio_3_assrt(N, results, table_mean_field_approx, sub, x, beta, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "\n",
    "beta = 0\n",
    "color_ = 'darkviolet'\n",
    "plot_scenaio_3_assrt(N, results, table_mean_field_approx, sub, x, beta, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "beta = 0.02\n",
    "color_ = 'darkorange'\n",
    "plot_scenaio_3_assrt(N, results, table_mean_field_approx, sub, x, beta, color_, marker_size, mean_field_marker_size)\n",
    "\n",
    "sub.set_xlabel(r'$\\alpha$', fontsize=x_label_size)\n",
    "sub.set_ylabel('max assortativity', fontsize=x_label_size)\n",
    "sub.tick_params(axis='both', labelsize=tick_size)\n",
    "sub.legend(fontsize=legend_size, loc='upper left')\n",
    "\n",
    "\n",
    "########################################################################################################################\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "personalized-running",
   "metadata": {},
   "source": [
    "# Removing improbable opinion shifts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "familiar-nevada",
   "metadata": {},
   "outputs": [],
   "source": [
    "N, T, topology_id, t_freq = 2000, 500000, 'random_geom', 25000\n",
    "\n",
    "t_freq = 25000\n",
    "\n",
    "m = 3\n",
    "possible_ops = np.array([-1, 0, 1])\n",
    "th_value = 0\n",
    "\n",
    "\n",
    "selectivity_rate, pers_rate  = -0.01,-0.01  #no selectivity and personalization\n",
    "\n",
    "\n",
    "in_ops_type = ('uniform', )\n",
    "#in_ops_type = ('manual', [0.1, 0.9])\n",
    "\n",
    "#load transition matrix\n",
    "transition_matrix = []\n",
    "for i in range(m):\n",
    "    transition_matrix.append(np.load(f'Transition matrices/Matrix_{m}_{i+1}.npy'))\n",
    "    #transition_matrix.append(np.load(f'Transition matrices/Matrix_{m}_{i+1}_second_iteration.npy'))\n",
    "    \n",
    "\n",
    "\n",
    "transition_matrix = [i.T for i in transition_matrix]\n",
    "\n",
    "transition_matrix[0][0] = [0.96, 0.04, 0]\n",
    "#transition_matrix[0][1] = [0.943, 0.057, 0]\n",
    "#transition_matrix[0][2] = [0.909, 0.091, 0]\n",
    "\n",
    "#transition_matrix[2][0] = [0, 0.082, 0.918]\n",
    "#transition_matrix[2][1] = [0, 0.07, 0.93]\n",
    "transition_matrix[2][2] = [0, 0.054, 0.946]\n",
    "\n",
    "transition_matrix = [i.T for i in transition_matrix]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "tight-chest",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6e1b3f31c85349ad8c364bdb7fb41c49",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(HTML(value=''), FloatProgress(value=0.0, max=500000.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "\n",
    "    \n",
    "\n",
    "results  = experiment_one_matrix(N, \n",
    "                                                     m, \n",
    "                                                     transition_matrix, \n",
    "                                                     in_ops_type, \n",
    "                                                     possible_ops, \n",
    "                                                     topologies, \n",
    "                                                     topology_id, \n",
    "                                                     selectivity_rate, \n",
    "                                                     pers_rate, \n",
    "                                                     th_value, \n",
    "                                                     t_freq, \n",
    "                                                     T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "matched-lambda",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x936 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pos, Ops, Ops_indices, public_opinion, pols, assrts, components_number, adj_matrices, t_measurements = results\n",
    "\n",
    "fig = plt.figure(figsize=(13, 13))\n",
    "sub = fig.add_subplot(1, 1, 1) # 3 rows, 2 columns, 1 cell\n",
    "#sub.set_title('A', fontsize=50, loc='left')\n",
    "\n",
    "\n",
    "sub.plot(np.arange(T+1), np.array(public_opinion[0])/N, color='darkorange', \n",
    "         label='$y_{1}(t)$', \n",
    "         linestyle='-', linewidth=5)\n",
    "\n",
    "sub.plot(np.arange(T+1), np.array(public_opinion[1])/N, color='darkgrey', \n",
    "         label='$y_{2}(t)$', \n",
    "         linestyle='-', linewidth=5)\n",
    "\n",
    "sub.plot(np.arange(T+1), np.array(public_opinion[2])/N, color='darkviolet', \n",
    "         label='$y_{3}(t)$', \n",
    "         linestyle='-', linewidth=5)\n",
    "\n",
    "sub.plot(t_measurements, pols, color='black', \n",
    "         label='polarization', \n",
    "         linestyle='-.', linewidth=5)\n",
    "\n",
    "sub.plot(t_measurements, assrts, color='darkgreen', \n",
    "         label='assortativity', \n",
    "         linestyle='-.', linewidth=5)\n",
    "\n",
    "sub.set_xlabel('$t$', fontsize=40)\n",
    "\n",
    "sub.set_xlim([0, T])\n",
    "sub.set_ylim([-0.05, 1.05])\n",
    "\n",
    "sub.tick_params(axis='both', labelsize=25)\n",
    "sub.legend(fontsize=20)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "thorough-spokesman",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Limiting values of public opinion variables:\n",
      "0.2865\n",
      "0.6055\n",
      "0.108\n",
      "Limiting value of polarization:\n",
      "0.6028805551610539\n",
      "Limiting value of assortativity:\n",
      "0.016025744085083813\n",
      "Max value of assortativity:\n",
      "0.04752473187209445\n"
     ]
    }
   ],
   "source": [
    "print('Limiting values of public opinion variables:')\n",
    "for i in public_opinion:\n",
    "    \n",
    "    print(i[-1]/N)\n",
    "    \n",
    "print('Limiting value of polarization:')\n",
    "print(pols[-1])\n",
    "\n",
    "print('Limiting value of assortativity:')\n",
    "print(assrts[-1])\n",
    "\n",
    "print('Max value of assortativity:')\n",
    "print(np.array(assrts).max())"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
